Вакансии

What you’ll do Participate in the Master Class Program designed to pivot experienced professionals into Life Sciences Consulting. Own key workstreams on customer-facing engagements early in the program to create high-impact business solutions. Collaborate with team members at all levels of Veeva to accelerate consulting skills development. Contribute to building effective business and operational improvement strategies powered by Veeva’s industry insights and technology. Support initiatives focused on speeding drug development, launching treatments more effectively, and shaping optimal customer engagement. Who you are You are graduating with an advanced degree or have 3-5 years of industry experience. You are excited to pivot your career into consulting for the Life Sciences industry. You are eager to join a program with an anticipated start date of April 2027. Requirements Advanced degree or 3-5 years of industry experience in a relevant field. Interest in transitioning into Life Sciences Consulting through the Master Class program. Ability to contribute to customer-facing engagements and collaborate across teams. Benefits & perks Structured Master Class program designed to accelerate consulting skills development. Exposure to industry-leading software, data, AI, and consulting expertise. Team description Veeva Business Consulting combines deep domain knowledge with innovative technology to help Life Sciences companies work more efficiently and connectedly. The team focuses on speeding drug development, launching treatments, and shaping stakeholder engagement using Veeva’s industry insights and technology. Location France (Master Class program, anticipated start April 2027).

Location: Mexico City AI Automation Analyst We're automating processes across the company using AI. AI is a powerful tool, but unlocking its full potential requires good data and well-structured business requirements. We're looking for someone who's ready to dive deep into the business context of different teams and help them drive AI-powered automation. Challenges that await you: Business Requirements & Discovery Gather and structure business requirements from different teams Translate business problems into clear, AI-ready specifications Build a deep understanding of each team's processes and pain points Prompting & Instructions Write and iterate on prompts for AI-driven workflows Write clear, unambiguous instructions for data labellers/annotators Continuously refine prompts and instructions based on output quality Analytics Build analytics to track automation performance and quality Identify patterns, gaps, and opportunities for further automation Turn findings into clear recommendations for the business What makes you a great fit: 0–3 years of experience — recent graduates are welcome to apply Strong mathematical/analytical background with a solid understanding of statistics Python and SQL knowledge is a plus English level B2 Genuine curiosity and willingness to learn and deeply understand business context

Location: Atlanta Workplace: OnSite Company Description We’re http://checkout.comCheckout.com http://Checkout.com. You might not know our name, but companies like eBay, Spotify, Klarna, Uber, and Sony do, because we’re behind many of the digital experiences you use every day. We are where the world checks out, enabling over 10 billion transactions yearly for more than one billion global shoppers. Whether you want to book a holiday, order food, renew a subscription, or check out online, there’s a good chance our tech powers the payments behind the scenes. Our platform helps the most ambitious businesses deliver effortless digital experiences, at scale. If you want to do career-defining work, you’ve come to the right place. We move fast, think globally, and believe great teams are built by hiring exceptional people with conviction, curiosity, and the desire to make an impact. With 20 offices across six continents and London as our HQ, we’re shaping the future of fintech – and we’re just getting started. At Checkout.com http://Checkout.com, we build the global payment infrastructure that empowers the world’s most innovative businesses to thrive. We are looking for an exceptional Underwriter to join our Atlanta team and play a pivotal role in our growth. In this role, you won’t just be ticking boxes—you will be a strategic partner. You will dive deep into complex enterprise business models, evaluate credit exposure, and balance risk with commercial opportunity. Operating at the intersection of Risk, Sales, and Legal, you will get unique, cross-functional exposure while working directly with some of our highest-value merchants. HOW YOU’LL MAKE AN IMPACT - Deconstruct Complex Business Models: Analyze enterprise-scale applications and apply creative evaluation techniques to unlock high-value, complex deals while adhering to internal risk guidelines. - Navigate High-Stakes Verticals: Confidently underwrite merchants in high-risk lines of business, including travel, ticketing, securities, and gaming. - Quantify & Mitigate Risk: Calculate credit exposure dynamically, tailoring your approach to the specific nuances of each merchant. - Drive Financial Diligence: Dissect P&Ls, balance sheets, and cash flow statements, applying a deep understanding of accounting principles to assess financial health. - Advise & Influence: Synthesize complex micro and macro risks into clear, balanced recommendations. You will present these insights directly to Senior Management, the Credit Risk Committee, and our partner banks. - Be the Face of Underwriting: Join forces with Sales and Account Management on customer calls, acting as a trusted advisor to our clients. - Enable Next-Gen Payouts: Assess and process applications for our innovative Pay to Card and Pay to Bank solutions. WHAT WE’RE LOOKING FOR - Proven Expertise: 4+ years of experience in merchant underwriting or a closely related financial analysis role. - Financial Acumen: Expert-level ability to assess diverse business models, analyze financial statements, and identify credit risk exposure. - A "Customer First" Mindset: Excellent communication skills with a knack for delivering creative, commercial solutions without compromising risk standards. - Collaborative Drive: A true champion of our "One Team" culture who builds bridges across cross-functional departments. - Decisive Execution: Strong escalation management skills—you act with urgency, take ownership, and resolve roadblocks effectively. - An Innovator's Spirit: A passion for operational excellence and a desire to actively contribute to broader departmental projects and process improvements. - Bonus Points: Familiarity with Customer Due Diligence, KYC, and KYB protocols is a strong plus. Additional Information Bring all of you to work We create the conditions for high performers to thrive, through real ownership, fewer blockers, and work that makes a difference from day one. Here, you’ll move fast, take on meaningful challenges, and be recognized for the impact you deliver. It’s a place where ambition gets met with opportunity, and where your growth is in your hands. We work as one team, and we back each other to succeed. So whatever your background or identity, if you’re ready to grow and make a difference, you’ll be right at home here. It’s important we set you up for success and make our process as accessible as possible. So let us know in your application, or tell your recruiter directly, if you need anything to make your experience or working environment more comfortable. Life at Checkout.com http://Checkout.com We understand that work is just one part of your life. Our hybrid working model offers flexibility, with three days per week in the office to support collaboration and connection. Curious about what it’s like to be part of our team? Visit our Careers Page https://www.checkout.com/careers to learn more about our culture, open roles, and what drives us. For a closer look at daily life at Checkout.com http://Checkout.com, follow us on LinkedIn https://www.linkedin.com/company/checkout/life/ and Instagram https://www.instagram.com/checkout_com/

Location: Algiers, Algeria Workplace: hybrid Context & Vision In 2026, writing code is no longer the primary bottleneck; managing its complexity and ensuring its reliability is. We are building a highly resilient advertising platform with a very lean, senior internal team, and we intend to keep it that way. To achieve scale without the overhead of a large engineering department, we rely on an AI-first development paradigm and a philosophy borrowed from the best large-scale open-source projects. Our code is not public, but our governance is theirs: asynchronous communication, exhaustive written documentation, explicit rules, and uncompromising quality gates. It is the only way a small team of humans and AI agents ships serious systems without accumulating technical debt. This role owns the data engine underneath the platform: the streams, segments and audiences that make advertising intelligent. The Role You will own the data and DMP layer end to end — the event streams flowing in, the segment and audience computation, and the analytical stores that feed targeting and reporting. What we hire for is judgment: the problems here are hard in the interesting way, and the interesting part is the tradeoffs you choose. 1. Hard problems, at real-time scale.Computing audiences and measurement over very large, high-velocity event streams, in near-real-time, where being right is not always the same as being exact and every choice has a real cost. We describe the problems; we expect you to bring the approach. 2. Stream-First Pipeline.Own the ingestion and processing pipeline. It is stream-first by design; you keep it that way rather than falling back to batch. 3. Segments & Audiences.Own how raw signals become targetable audiences — how they are computed, stored, refreshed, and exposed to the serving path. This is the intelligence layer of the product. 4. AI-First Delivery & Governance. We expect AI to write most of the code; you are the editor, not the typist. You specify work as explicit, self-sufficient issues, direct agentic tooling to implement, and gatekeep every diff. Schemas, data contracts and Architecture Decision Records are documented. If it is not written down, it does not exist.  The Tech Environment - Data: event streaming and stream processing, relational and analytical stores. - Language: the codebase is a compiled systems language; we care more about how you reason about data than about the language you arrive with. - Domain: DMP, segments, audiences, identity, measurement. - Cloud: Google Cloud Platform, Kubernetes. Profile & Requirements We are looking for a data-minded engineer who frames a problem before reaching for a tool, owns correctness, and thrives in a lean, high-quality environment. This role is not suited to someone who wants a narrow, hand-fed scope inside a large team. Essential Experience - 5+ years building data or backend systems in production, with genuine ownership of a pipeline's reliability and the correctness of its output. - Depth on hard data problems— you have built things where scale, real time, or accuracy made the design non-obvious, and you can talk through the tradeoffs you chose and why. - Streaming experience and a real grasp of stream-vs-batch tradeoffs, event modelling, and schema evolution. - Comfort in a compiled systems language (Rust, Go, C++, Scala or similar). The codebase is Rust; the language is the tool, the data thinking is the skill. - Working knowledge of an analytical data store and SQL. DMP / ad-data or audience/segmentation experience is a strong plus. Core Competencies & Mindset - Judgment over recipes: you frame a data problem and its constraints before choosing an approach, and you can say when an approximate answer is the right engineering call and when it is not. - Distributed & complex systems: knowledge of, and a taste for, distributed and complex systems is very welcome. Tell us about the ones you have built or operated — what made them hard. - AI Development Lifecycle: genuine proficiency editing and validating AI-produced code, and decomposing ambiguous goals into specifications an agent can execute unattended. - Uncompromising Quality: a maniacal focus on data correctness, freshness, and reliability. A wrong number that ships is a wrong number the business trusts. - Written & Asynchronous: exceptional written communication; effective in a distributed, async environment (Paris timezone +/- 3h). - Ownership: you own your pipeline and its documentation completely, and you surface problems before they are asked about.

Uzum Market — крупнейший и самый быстрорастущий онлайн-маркетплейс в Узбекистане, часть цифровой экосистемы Uzum. Ищут тимлида аналитики на направление Warehouse Efficiency & HR Ops. Стрим отвечает за массовый персонал, эффективность складских операций, снижение потерь и брака в маркетплейсе. Это не классическая продуктовая аналитика — меньше A/B-тестов, больше работы с операционными процессами: диагностика проблем, внедрение изменений, оценка их эффекта на бизнес, включая применение квази-экспериментальных методов (DiD, Causal Impact и др.). Есть классный офис в Ташкенте, возможна полная удалёнка, зрелая команда и много задач, где аналитика напрямую влияет на бизнес.

Location: Brazil; Argentina; Honduras Workplace: Remote ABOUT THE ROLE We’re splitting our Analytics & Reporting group into two focused teams: a Data Engineering team that owns data acquisition and the company-wide data platform, and an App team that owns everything our customers touch, including the data-serving APIs, the Analytics section of the Uberall platform, and the reports that turn location data into decisions. We’re hiring the lead for the App team. You’ll be a player-coach: you’ll manage and grow a team of six engineers (3 backend, 2 frontend, 1 QA), partner daily with two Product Managers, a Designer, and a UX Researcher, and stay meaningfully hands-on. Roughly 20–30% of your time is spent on architecture, code reviews, and code. You’ll work as a peer to the Lead Data Engineer, with a close, explicit contract between your team’s customer-facing products and the data platform that feeds them. This is a role for someone who has led before and still loves to build. WHAT YOU’LL OWN - Customer-facing data APIs: the public APIs enterprise customers use to access their data, and the microservices behind them. - The Analytics product: the Analytics section of the Uberall platform, including its frontend, filtering experience, and the APIs powering custom reports. - Customer reporting: the QuickSight reports our customers rely on, and the gold-layer datasets that feed them. Your team owns its data models end-to-end, built on the self-serve platform the Data Engineering team provides. - Production: you build it, you run it. Your team deploys and operates its own services (Kubernetes on AWS), owns its observability and SLOs, and runs its own on-call rotation. You lead the incident process. - The team: hiring, growth, 1:1s, delivery, and the engineering culture of a newly formed team. With one QA engineer among six, you’ll make quality everyone’s job. WHAT YOU’LL DO IN YOUR FIRST YEAR - Stand up the App team as a healthy, autonomous unit: clear ownership, sustainable delivery cadence, and strong working relationships with Product, Design, and the Data Engineering team. - Co-own, from the application side, the in-flight migration of data pipelines out of our monolith and into the Data Engineering stack. Your backend engineers keep those pipelines running and hand them over cleanly, so your team can focus fully on APIs and product. - Drive the modernization of our backend estate: the stack is consolidating on Kotlin, and legacy Groovy and Scala services need a pragmatic path forward. - Shape the next chapter of Analytics: AI-assisted insights in the product, and exposing your team’s data and APIs for consumption by AI agents through the company’s data gateways. WHAT WE’RE LOOKING FOR - 7+ years of software engineering experience, with deep backend expertise on the JVM (Kotlin strongly preferred; our stack: Kotlin, Spring Boot, Postgres). - 2+ years leading an engineering team with genuine people responsibility (hiring, 1:1s, performance, and delivery) while staying hands-on. - Experience designing, operating, and evolving microservices in production: Kubernetes, AWS, observability, SLOs, and incident management. You’ve run an on-call rotation, not just been on one. - Strong SQL and analytical data modeling skills. Your team owns the datasets behind customer reports, and you can reason about them credibly. - Experience with RESTful, service-oriented architectures serving external customers at scale. - Enough frontend fluency (React, TypeScript) to lead frontend engineers well. You review their thinking, not their semicolons. - Experience navigating legacy systems and migrations. You can modernize without stopping the world. - Professional working English (read, write, speak) and comfort collaborating across a remote, distributed organization. NICE TO HAVE - Experience with Groovy, Scala, or Python - the languages of our existing services. - Experience with BI tooling (Amazon QuickSight or similar) and data warehouse platforms (Databricks, Snowflake, Redshift). - Experience building LLM-powered product features or exposing data/APIs to AI agents.

Location: New York, New York, United States About the Role iCapital is looking to hire an Analyst to join the Structured Investments team to focus on sales support. This position will work cross-functionally and closely with bank issuers and clients. Responsibilities Conduct calls to set appointments for licensed sales professionals. Learn iCapital products and prepare to effectively communicate the objectives, risks, features, and benefits of these products. Analyze regional and product sales trends within participating broker-dealer firms and among individual Financial Advisors. Make 50+ outbound calls per day. Learn financial markets and portfolio strategies. Assist senior sales professionals within assigned territory. Effectively partner with the external wholesaler and the regional distribution team. Utilize contact management systems to capture information and schedule follow up activities. Prepare for and pass necessary licenses. Qualifications Bachelor's degree is required 0-2 years of relevant experience Sales and client service experience, within the financial services industry is a plus Excellent relationship, follow-up, and communication skills General knowledge of the financial services industry Motivated, mature, trustworthy, and a team player Highly organized and able to prioritize in a fast-paced environment Knowledge of private markets, structured products, and options is a plus Series 7, 63 and SIE (FINRA) licenses or candidate must obtain licenses within 4 months of hire date Benefits The base salary range for this role is $60,000 to $65,000.  This position is paid on an hourly basis and is classified as non-exempt. Employees in this role are eligible for overtime pay in accordance with applicable law. iCapital offers a compensation package that includes equity for all full-time employees and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer-matched retirement plan, generously subsidized healthcare with 100% employer-paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and paid time off (PTO). We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday. For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/ iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Location: United Kingdom (Hybrid); United Kingdom (Remote); United States Workplace: Remote Most money apps talk at you. Cleo talks back ✨ We're not building another finance app. We're building the world's first AI financial assistant, one that actually understands your money and makes you better at it, and we're changing the world's relationship with money in the process 💰 For everyone, whatever their background or balance. The proof: profitable, fast-growing, a unicorn with over $300M in ARR, and millions of people who now feel differently about their money. We love original thinkers who challenge the status quo. We move fast, tell the truth, and there's nowhere to hide from good work here. If that excites you more than it scares you, you'll fit right in. Follow us on LinkedIn https://www.linkedin.com/company/cleo-ai/ for new features and the occasional roast 🔥 MEET THE TEAM 👥 Here at Cleo we have team of ~135 member in our Borrow Pillar and ~8 dedicated to Credit Policy and Analytics. This function brings together several specialisms, all working toward managing portfolio performance; designing the systems, models, and controls that make lending sustainable. They drive to build and grow a portfolio of responsible EWA & Pay Later products that can scale across markets while protecting users from high cost debt trap. ABOUT THE ROLE ✍️ We're hiring a Head of Data Science to lead credit performance measurement and monitoring within our Risk & Payments pillar. This is a player-coach role: you'll manage a team of Credit Data Scientists and Analysts, splitting your time between hands-on analysis and leading the team - setting direction, developing people, and owning the function's output. You'll own the frameworks and metrics that keep our credit products healthy, and drive the deep-dive analyses that explain performance shifts and turn them into action. Key areas of impact: - Own credit performance measurement - design and maintain Cleo's risk metric framework (arrears, default, yield, LTV, marginal loss), and the dashboards/alerts that catch arrears spikes, roll-rate shifts, and decisioning anomalies early. - Bridge model health and business decisions - partner with Risk Modelling to translate model metrics (AUC, PSI, calibration, drift) into policy and product recommendations, and diagnose whether performance moves are model-driven, macro, or operational. - Lead root-cause analysis - own investigations end-to-end (question → analysis → recommendation) on issues like arrears spikes or yield compression, using driver analysis (SHAP, feature importance, decomposition), and present findings to Risk, Product, and Leadership. - Support policy and decisioning - work with Credit Policy and Decision Science to build evaluation frameworks for policy changes, quantify their marginal impact, and support elasticity/profitability modelling on pricing and limits. - Manage and develop a team - directly manage Credit Data Scientists and Analysts: set priorities, manage performance, and grow the team, not just direct project work. WHAT WE'RE LOOKING FOR 🕵️ - Strong SQL and Python skills, comfortable working directly from the warehouse - Track record owning analyses end-to-end - from framing the question to shipping a recommended change - Hands-on experience with predictive models (credit, fraud, or similar), fluent in AUC/Gini, calibration, PSI/CSI, and drift - Fluency in credit portfolio metrics (arrears buckets, roll rates, loss rate, yield/marginal loss) and how they tie to unit economics - Experience directly managing analysts or data scientists - priorities, performance, and people development - Nice to have: experience with short-term or revolving credit products - Nice to have: experience with both UK and US regulatory frameworks WHAT WE OFFER We offer benefits package built to support you in and out of work. Benefits vary by country 🌍 and include meaningful equity, comprehensive health insurance, mental health support, a paid one-month sabbatical after four years, a learning & development platform, pension or retirement contributions, and location-specific leave entitlements. For the full breakdown on what's available in your location, visit our Candidate Hub https://meetcleo.notion.site/Cleo-Candidate-Hub-3b95c63b874580e9a068fdc6c8929ebf 👈 WHAT MATTERS Cleo's mission is to change the world's relationship with money. We can't do that without building a brilliant, genuinely diverse team - and making sure our hiring process gives everyone a fair shot, running a fair and transparent recruitment process in which every candidate is considered on their merits. We're glad to make reasonable adjustments at any stage of the process. If there's anything we can do to support you in showing us your best, please let your recruiter or one of the team know. We may use AI-assisted tools during the recruitment process to take support the team in different ways like taking notes or referring back to conversations. They do not replace the team and all applications are reviewed by a Cleo employee thoroughly!

Задачи: — Подготовка ежемесячных управленческих отчетов и поддержка закрытия месяца. — Помощь с финансовой отчетностью, сверками и ведением точных финансовых записей. — Поддержка внешних аудитов и финансового соответствия. — Помощь в бюджетировании, прогнозировании и анализе отклонений. — Мониторинг финансовых показателей и предоставление аналитики для поддержки бизнес-решений. — Подготовка отчетов для руководства и проведение разовых финансовых анализов. — Поддержка ежедневных казначейских операций, мониторинг денежных потоков и операций с платежами. — Выполнение сверок между банками, платежными провайдерами и внутренними счетами. — Улучшение финансовых процессов и усиление финансового контроля. — Обеспечение поддержки клиентов по вопросам платежей, включая отслеживание задержанных или отсутствующих платежей, помощь с проблемами платежей и консультации по платежным и банковским деталям. — Расследование операционных проблем и координация с командами инженерии и управления аккаунтами для решения вопросов функциональности и обработки платежей. — Обеспечение высокого уровня клиентской поддержки и помощь в улучшении внутренних процессов и общего клиентского опыта. Требования: — Опыт работы 3+ года в финансах, бухгалтерии, управленческом учете, аудите, казначействе или финансовых операциях. — Глубокое понимание принципов бухгалтерского учета, финансовой отчетности и управленческой отчетности. — Опыт в бюджетировании, прогнозировании, сверках и финансовом анализе. — Сильные аналитические навыки, внимание к деталям и проактивный подход. — Опыт работы в финтехе, банковской сфере, платежах, финансовых услугах или в одной из Большой четверки будет преимуществом. — Уровень английского языка B2+. Желательно: — Опыт работы с бухгалтерскими системами, такими как Xero, QuickBooks, NetSuite или аналогичными. — Знакомство с казначейством, платежами или мультивалютными финансовыми операциями. — Наличие или обучение по сертификатам ACCA, CIMA, CPA, ACA (завершено или в процессе).

Задачи: — Подготовка ежемесячной управленческой отчетности и поддержка закрытия месяца. — Помощь с финансовой отчетностью, сверками и ведением точных финансовых записей. — Поддержка внешних аудитов и финансового соответствия. — Помощь в бюджетировании, прогнозировании и анализе отклонений. — Мониторинг финансовых показателей и предоставление аналитики для поддержки бизнес-решений. — Подготовка отчетов для руководства и проведение разовых финансовых анализов. — Поддержка ежедневных казначейских операций, мониторинг денежных потоков и операций с платежами. — Выполнение сверок между банками, платежными провайдерами и внутренними счетами. — Улучшение финансовых процессов и усиление финансового контроля. — Поддержка клиентов по вопросам платежей, включая отслеживание задержанных или пропавших платежей, помощь с проблемами платежей и консультации по платежным и банковским деталям. — Расследование операционных проблем и координация с командами инженерии и управления аккаунтами для решения вопросов с платежной функциональностью и обработкой. — Обеспечение высокого уровня клиентской поддержки и помощь в улучшении внутренних процессов и общего клиентского опыта. Требования: — Опыт работы 3+ года в финансах, бухгалтерии, управленческом учете, аудите, казначействе или финансовых операциях. — Глубокое понимание принципов бухгалтерского учета, финансовой отчетности и управленческой отчетности. — Опыт в бюджетировании, прогнозировании, сверках и финансовом анализе. — Сильные аналитические навыки, внимание к деталям и проактивный подход. — Опыт работы в финтехе, банковской сфере, платежах, финансовых услугах или в одной из "Большой четверки" будет преимуществом. — Уровень английского языка B2+. Желательно: — Опыт работы с бухгалтерскими системами, такими как Xero, QuickBooks, NetSuite или аналогичными. — Опыт в казначействе, платежах или мультивалютных финансовых операциях. — Наличие или обучение по сертификатам ACCA, CIMA, CPA, ACA.

Задачи: — Отвечать на вопросы студентов в чате и помогать с трудностями на протяжении всего обучения. — Проводить воркшопы — онлайн-занятия по заданному шаблону с активным участием студентов, модерировать, инициировать диалог, отвечать на вопросы. — Помогать и направлять студентов ставить цели, рефлексировать, делать выводы и быть самостоятельными. — Проводить Q&A-сессии — онлайн-занятия свободной формы, на которых студенты задают вопросы по инструментам и специфике их использования. Требования: — Действующий 1С-аналитик или функциональный архитектор с опытом от 4-х лет. — Участие в проектах внедрения с командой от 4-х человек. — Желание делиться опытом и навыками с начинающими специалистами. — Владение ключевыми темами курса или готовность быстро в них разобраться: понимание жизненного цикла проекта и роли 1С-аналитика на каждом этапе, участие в проектах на разных этапах. — Сбор требований к ПО, знание принципов целеполагания, различных техник выявления требований, моделирование бизнес-процессов as-is и to-be. — Разработка требований к ПО. — Владение языком запросов 1С на базовом уровне (выборка из одной или нескольких таблиц). — Понимание возможностей платформы 1С, знание одной или нескольких конфигураций 1С на продвинутом уровне. Условия: — Удаленное сотрудничество с возможностью работать из любой точки мира. — Возможность освежить знания, реализовать потенциал и влиять на качество образования в индустрии. — Развитие мягких навыков: умение выступать публично, давать обратную связь, объяснять сложные вещи простыми словами и формировать безопасную образовательную среду. — Бесплатное обучение в Школе наставников и плавное погружение в сотрудничество. — Выдача сертификатов о социально-полезной деятельности. — Возможность писать статьи и участвовать в конференциях, мероприятиях и подкастах Яндекс Практикума.

Location: United States SaaS Revenue & Financial Analyst — Flosum About Flosum Flosum is a Salesforce-native platform company delivering enterprise-grade DevOps, data protection, and security solutions to some of the world's largest organizations. Our product portfolio spans Cloud DevOps, Data Migrator, Data Masking, Data Backup, Org Security, Cloud Trust Center, and Sandbox Synchronization — all built natively on the Salesforce platform. We serve enterprise customers across technology, energy, financial services, healthcare, and federal government. Flosum is a growth-stage company operating with the intensity and speed of a startup backed by the discipline of a mature operator. The Role We're hiring a SaaS Revenue & Financial Analyst who will own the measurement layer of our entire business. You will be the person who knows every number — ARR, net retention, expansion, churn, pipeline conversion, cost of acquisition, gross margin by product line, services margin, cash flow, and everything in between. You'll work across Salesforce (our CRM and billing system of record) and QuickBooks (our financial system) to build a unified, always-current picture of company performance. This is not a reporting role. This is an analytical role where you connect revenue operations data to financial outcomes and surface the insights that drive decisions at the CEO level. What You'll Own You will build and maintain our SaaS metrics infrastructure — ARR waterfall, cohort retention analysis, revenue recognition schedules, deferred revenue tracking, and unit economics by segment. You will reconcile Salesforce bookings data against QuickBooks revenue entries and ensure we have a single source of truth across both systems. You will produce monthly and quarterly financial and revenue packages for leadership, including variance analysis against plan. You will model scenarios for pricing changes, product bundling, geographic expansion, and headcount investment. You will monitor pipeline health and translate pipeline data into revenue forecasts with documented assumptions. You will own the data integrity between our CRM and accounting systems, flagging discrepancies before they compound. You will support board-level and investor-level reporting with clean, defensible metrics. Requirements What We're Looking For You have three-plus years of experience in SaaS financial analysis, revenue operations, or FP&A at a B2B software company. You are deeply proficient in Salesforce — not as a user, but as someone who understands opportunity objects, product schedules, contract structures, and reporting at a data level. You are equally proficient in QuickBooks Online, including chart of accounts design, revenue categorization, journal entries, and reconciliation workflows. You understand ASC 606 revenue recognition principles and can apply them to a multi-product SaaS business with annual and multi-year contracts. You can build financial models from scratch in Excel or Google Sheets — not from templates, from logic. You think in terms of cohorts, not just totals. You understand the difference between bookings, billings, and revenue, and you can explain why each matters. You are precise, skeptical of your own numbers, and obsessive about data integrity. Preferred Experience at a company with a mix of subscription revenue and professional services. Familiarity with Salesforce CPQ or native Salesforce quoting and contract objects. Exposure to investor or board reporting at a growth-stage company. Experience with Marketo or HubSpot data as it relates to CAC and attribution modeling. Why Flosum You'll report directly into the CEO's operating rhythm. Your work will not sit in a queue — it will shape hiring plans, product investment, and go-to-market strategy in real time. Flosum is building the definitive platform for Salesforce lifecycle management, and we need someone who can measure every dimension of that growth with precision.

Location: U.S. (Remote) Workplace: Remote ABOUT CLIPBOARD Our mission is to uplift as many communities as possible. We do this through our app-based marketplace that connects healthcare professionals with the workplaces that need amazing workers. This enables hundreds of thousands of people to achieve financial stability for themselves and their families while providing essential care to millions of people across the U.S. Founded in 2016, we are a remote-first team of over 1,000 people building a top Y-Combinator company https://www.ycombinator.com/topcompanies/ and have been profitable since 2022. We’re the leader in Long-Term Care staffing and are rapidly expanding into Home Health, Hospitals, and more, meaning we have more work to do than people to do it, and are growing our team to support millions more people and their communities. ABOUT THE ROLE: As a Documents Compliance Analyst, you own the compliance decisions behind whether a healthcare professional is cleared to work: background check disqualifications, credential and risk review, and how new state requirements get implemented. You set the standard the team applies, and you are the named decision-maker when a case is hard. What the law requires is a given. How we meet it is up to you, and you own that call. This is not a people management role. The work is recurring by design. The same categories of questions arrive every week, alongside state license renewals and reporting that run on a fixed calendar and never finish. Your value is in reaching the same well-reasoned decision every time and documenting your reasoning well enough that others can apply it. You'll work closely with Agents, SMEs, Team Leads, and Legal, none of whom report to you, so your credibility comes from the quality and consistency of your judgment rather than from authority. You will report to the Head of the Documents Team. WHAT YOU’LL OWN Judgment and decisions - Serve as the named escalation point for background check disqualification decisions - Make the initial call on agency compliance implementation - Handle escalations on worker credential verification, including license violations and reprimands - Decide which questions you resolve and document yourself, and which warrant partnering with Legal Written analysis - Produce risk analyses in a consistent format: the question, your research, your reasoning, your recommended path. - Evaluate new state and agency requirements before implementation, quantifying what compliance costs a worker in time, money, and completion rate, and recommending how we implement. - Build and maintain the decision record that lets other people reach the same conclusion you would Recurring compliance operations - Own the credential verification audits - Plan and drive the implementation of high-value requirements, such as continuing education - State license renewals - Ongoing state reporting REQUIREMENTS: - Bachelor’s degree. - At least 5 years of professional experience. - Prior experience in a role where you applied regulations to real decisions. Examples: - regulatory or compliance-focused paralegal - regulatory compliance specialist - legal analyst - background screening adjudicator - trust and safety or eligibility policy at a marketplace - Experience interpreting statutes, regulations, or agency guidance and turning them into operational requirements. WHAT WE’RE LOOKING FOR: - You can reach a defensible decision when documentation is incomplete or unavailable, and you're explicit about what your reasoning rests on. - You can read complex regulatory material and work out how it applies in practice to a marketplace model. - You weigh compliance risk against business impact and find the path that meets the requirement without restricting more than it demands. - You write decision memos and business cases that leadership can act on. - You build credibility with people who don't report to you. - You own recurring work with hard deadlines, such as license renewals and state reporting. - Willingness to maintain overlapping working hours with Eastern and Pacific time (ET/PT). NICE TO HAVE: - Compliance, regulatory, or licensing experience in healthcare, staffing, or another regulated industry. - Experience at a government or regulatory agency. - Experience with independent contractor or marketplace models. - Experience with background check adjudication or adverse action processes. - Experience with state licensing filings. SYSTEM REQUIREMENTS - Minimum 15Mbps wired internet connection - Minimum i5 processor or equivalent - Minimum 12GB RAM - Dedicated, quiet working environment - Reliable power source and backup internet connection Quick Note on Scammers: Clipboard would never ask you for money or your bank details to participate in our hiring process. Report any scammers impersonating the Clipboard hiring team members here https://forms.gle/SyGaxHFbon7Hg9fW6.

Location: Colombia Reports to: Executive Director Location: Fully Remote About the Company Our client is a fast-growing, forward-thinking organization focused on reimagining how businesses operate through innovation, care, and agility. Their culture emphasizes collaboration, transparency, and trust, with a strong focus on empowering team members to take ownership, share ideas openly, and grow alongside the business. They value speed, adaptability, and continuous learning, and they celebrate progress and wins at every stage. About the Role The Finance & Data Analytics Manager will serve as the strategic owner of the company’s financial visibility and business performance insights. This role is responsible for overseeing financial operations while transforming data into actionable intelligence that supports decision-making across leadership, sales, and operations. The position blends finance, analytics, and operational reporting, with ownership over forecasting, financial reporting, sales analytics, and cash flow visibility. Success in this role requires the ability to connect financial data with operational outcomes and ensure leadership has clear, timely insights to act with confidence. Responsibilities Manage and analyze sales, expense, and performance data to produce clear, data-driven insights Build and maintain dashboards and financial models that track overall company health and sales performance Oversee bookkeeping and ensure financial records are accurate, organized, and current Lead payroll review, billing, and payment processes with a focus on accuracy and timeliness Review and process agent invoices and commission calculations Reconcile accounts and track inventory across systems to ensure data consistency Partner with leadership on revenue forecasting, growth modeling, and KPI tracking Identify opportunities to improve processes and automate finance and reporting workflows Experience & Education 5+ years of experience in finance, FP&A, or data analytics roles Experience in e-commerce, DTC, or fast-moving startup environments Bachelor’s degree in Finance, Accounting, Economics, Data Analytics, or a related field Advanced proficiency in Excel/Google Sheets (pivot tables, dashboards, automation) Experience with financial and reporting tools (e.g., QuickBooks, Airtable, Power BI) Familiarity with workflow and automation tools such as Zapier, n8n, and Make Comfortable working with project and data visualization tools like Asana, Vibe Canvas, and Lucid Experience integrating data across systems to create unified dashboards or reporting flows Certifications (Preferred, Not Required) CPA, CFA, or data analytics-related certification

Location: Almaty, Kazakhstan Workplace: OnSite WHY WORK AT HIGGSFIELD AI? Higgsfield AI is the fastest-scaling generative AI company in history, hitting $1B in annual revenue run rate, 25M+ users worldwide, 6M+ generations per day, and powering 390 of Fortune 500 brands. We're building at the absolute frontier of AI-powered video creation and next-generation creative tools. Joining Higgsfield means becoming part of a high-impact team shaping the future of AI-native experiences, at a company that isn't just moving fast, but rewriting what fast looks like. WHAT THIS ROLE MEANS AT HIGGSFIELD This role owns how Higgsfield measures its product - from the first sign-up to whether people come back. You are the measurement owner for onboarding, first generation, the paywall, plans and credits, and retention. Product managers ship fast here - your job is to make sure they ship knowing. You make sure: - Every product decision has a number attached to it before it ships and after it ships - Experiments are designed to be readable, and then read honestly - including when the answer is “this didn’t work” - The events the product emits can be trusted; you own the definition, not just the query - A PM gets an answer in hours, not next sprint You are the person who decides what “it worked” means. WHAT YOU WILL DO Product measurement - Own the core product metrics: activation, first-generation success, generation depth, free→paid conversion, repeat usage, retention by cohort and segment. - Define each metric once, write the definition down, and hold the line on it - one definition across dashboards, decks, and Slack. - Instrument new features before launch, with product and engineering: which events, which properties, what success looks like, when we call it. - Watch the health of the event stream itself - tracking drift, double counting, missing parameters, naming breakage and find the problem before a decision gets made on top of it. Experimentation - Design A/B tests properly: hypothesis, one primary metric, unit of randomization, MDE, sample size, run length, guardrail metrics. - Read them honestly: significance, peeking, novelty effects, sample-ratio mismatch, segment heterogeneity. - Separate “we proved this works,” “we proved this doesn’t,” and “we can’t tell from this test” - and say which one out loud. Product & monetization analysis - In-product funnel work: onboarding and quiz, first generation, paywall, checkout, plan choice, credit top-ups. - Pricing and packaging analysis: plan mix, credit consumption, unit economics per generation, margin by feature and by model. - Feature adoption and its real effect on retention and revenue — separating “users who do X retain better” from “making people do X improves retention.” - Behavioural segmentation: casual creators vs corporate/B2B, new vs returning, by model and by use case. Mixing them hides everything that matters. Making it usable - Build the few dashboards PMs actually open on their own — decision-shaped, not comprehensive. - Write short readouts a non-analyst can act on. Visualize data for humans, not for other analysts. - Automate recurring reporting so your hours go to new questions, not refreshes. - Work in SQL, Python, BigQuery and product analytics tools. We use AI heavily - resourcefulness beats syntax. WHO WE'RE LOOKING FOR We're looking for an analyst with opinions. You should have: - Strong SQL: window functions, cohorts, funnels and retention on raw event data, without help. - Python at working level for analysis (pandas, notebooks). Entry level is fine - we use AI heavily. - Real experimentation experience: you have designed tests, run them, and killed features with the results. - Statistical honesty: you know what a p-value does and does not entitle you to say, and you have refused to call a flat test a win. - Understanding of subscription + one-time purchase mechanics: recurring vs one-off revenue, refunds, plan changes, deferred value of unspent credits. - The instinct to check the instrument before explaining the movement - a surprising number is a claim, not a fact. - Ownership: you decide what's worth analyzing, you chase the fix, you follow the recommendation to a shipped change. - Clear written and spoken English, B2+. Backgrounds that often do well: - Product analysts from consumer subscription or PLG products - Growth/BI analysts who moved into product and stayed - Early-startup analysts who built product measurement from zero - Data scientists who got tired of models and want decisions WHAT THIS ROLE IS NOT This role is not a fit if you: - Wait for a ticket to tell you what to analyze - Want to build models more than you want to change decisions - Need a data engineering team and clean tables to exist before you can start - Would report a lift you don't believe in because a stakeholder wants it - Need perfect data before you can say anything useful - Want predictable 9–5 workdays HIRING PROCESS - Screening call (30 min) - Hiring-manager screen (30 min) - Business case (1 hour) - Take-home with real-shaped data (7 days, ~10–12 hours of work) - Team interview (60 min) - Paid on-site trial (1 month) WHAT WE OFFER - Competitive base salary in USD, based on your experience, skills, and the scope of the role. - Equity participation through the company’s stock option program, giving you the opportunity to share in Higgsfield’s long-term growth. - Relocation support to Almaty for candidates moving from another city or country. - A highly collaborative, fast-paced environment where you can work directly with experienced leaders and have a meaningful impact on the product and company. - Opportunities for professional growth, ownership, and career development as the company scales. - Company-provided equipment, meals, transportation, or other office benefits.

Location: London, United Kingdom Workplace: none About InvestEngine We’re a ~200-person, AI-first fintech. We move fast, we expect people to own things end to end, and we don’t have a lot of specialist support infrastructure to hide behind — if you spot a gap, you’re expected to close it, not escalate it and wait. About the role We’re hiring our first dedicated Analytics Engineer at InvestEngine. This is a foundational hire: you’ll sit at the intersection of data engineering, analytics engineering, and business partnership — turning raw, disparate data into governed, trustworthy models that the rest of the company makes decisions on. You won’t just write dbt models in isolation. You’ll work directly with stakeholders across the business — Product, Engineering, Risk, Finance, Investment, Marketing — to understand the problems they’re actually trying to solve, then design and ship the pipelines, models, and semantic layer that solve them. You’ll also help shape how we use AI-enabled tooling to make the whole analytics function faster, and how we structure our data so that AI tooling can be trusted to answer questions about it. We’re actively modernising our data stack, and we want the person in this role to shape it. Some of it is in place, some of it is being rebuilt, and some of it hasn’t been decided yet. If you have informed opinions about orchestration, ingestion, testing, semantic layers, or BI — we want to hear them. Who thrives here We’ve pitched this at mid to senior level , but the honest position is that the level matters less than the appetite. The ultimate test is hunger, and the desire to shape this space and have real impact . If you’re technically strong but hungrier than your years of experience suggest, apply anyway — we’d rather have someone who wants to own this than someone who has simply done it before somewhere bigger. Beyond that, this role suits someone who: Operates well with ambiguity and limited structure. You’ll be the first analytics engineer here — no existing playbook, no dedicated data engineering team to lean on, no established BI function to slot into. You’ll be building a lot of it as you go. Wants a small, fast company on purpose — not just escaping bureaucracy elsewhere, but genuinely drawn to the trade-off: more ownership and visibility, less process and hand-holding. Lives in the tools, not in email chains. You default to GitHub, dbt, Slack/Notion, and automation over status meetings and Word docs. Can point to things they’ve actually built and shipped , not just designs or concepts they contributed to. Already uses AI to do the job better — Claude, Copilot, or similar — and is curious about where it can go further. Learns fast. We care more about how quickly you close a knowledge gap than how complete your CV looks today. Works well directly with Product, Marketing, Operations, and Engineering , not just with other analysts — this role sits right at that boundary. Our values Everyone at InvestEngine is expected to live these, and this role will be assessed against all five: Act like an owner — you take responsibility for outcomes, not just tasks Keep improving. Stay curious. — you push your own standards and the team’s, and you’re genuinely curious about better ways to work Achieve more together — you make the people around you (business stakeholders included) more effective, not just yourself Speak up. Share openly. — you flag risks, disagreements, and better ideas rather than sitting on them Put customers first. Create real value. — you build things because they solve a real problem, not because they’re interesting to build What you’ll do Analytics engineering & the semantic layer Design, build, and maintain dbt Core models that transform raw data into clean, well-tested, well-documented datasets Own and evolve our semantic layer — consistent metric definitions, business logic, and naming that the whole company can trust and query against Establish and enforce data modelling standards, testing practices, and documentation as the function scales Evaluate and help roll out modern BI tooling — experience with Lightdash, Omni, Looker, or Metabase all translates well — to make metrics genuinely self-serve for non-technical stakeholders Building the AI context layer Structure our models, metric definitions, documentation, and lineage so they’re machine-readable, not just human-readable — because our semantic layer is what AI tooling reasons over Make AI-driven analytics reliable: if two people (or two agents) ask the same business question, they should get the same answer, because the definition lives in one governed place Treat naming, documentation, and metric definitions as first-class engineering deliverables rather than afterthoughts, since they directly determine how trustworthy our AI-enabled BI is Use Claude to accelerate development — model scaffolding, code review, documentation, QA, and pipeline debugging — and Notion AI to keep documentation and runbooks current and genuinely useful Bring a point of view on where AI can responsibly speed up analytics engineering, and help the wider team adopt it well Data engineering & the platform Build and maintain ingestion and transformation pipelines across our stack. We use a modern data stack, such as AWS, Redshift, and Airflow Write production-quality Python for extraction, transformation, and automation tasks that fall outside dbt’s remit Help us modernise: we’re actively evolving this stack and expect you to challenge and improve it, not just operate it Warehouse cost & performance Own the performance and cost profile of our Redshift warehouse — you should be able to read a query plan, choose sensible sort and distribution keys, and design incremental models without being asked Spot and act on opportunities to reduce complexity and cost across our models and pipelines, rather than letting spend and technical debt accumulate quietly Make deliberate trade-offs between freshness, cost, and complexity — and explain those trade-offs to the business in terms they care about Data quality & observability Champion analytics engineering best practice across the company: testing, version control, code review, CI, and documentation applied to data the same way engineering applies them to software Build and own data quality, freshness, and pipeline monitoring so problems are caught by us before they’re caught by a stakeholder looking at a dashboard Set the standard for what “trustworthy data” means here, and hold the line on it as the volume of models and requests grows Upstream influence Work with our engineering teams to make sure application and event design accommodates reporting and analytics requirements before data reaches the warehouse — good analytics starts at the source, not in the transformation layer Influence payload and schema design for new services and product features, so we’re not permanently reverse-engineering business meaning out of operational tables Support analysts and business users with automation, tooling, and data engineering expertise, and provide training and guidance on how to use our data well Business partnership Work directly with stakeholders to understand their problems, not just their requested outputs — translate ambiguous business questions into pipeline and modelling requirements Act as a trusted advisor on what’s possible with our data, and push back constructively when a request doesn’t solve the underlying problem Support financial, operational, and regulatory reporting needs appropriate to a regulated investment platform Governance Apply our data classification and access model when onboarding sources: identify PII (including in free-text fields), decide what belongs in the sanitised analytics layer versus a restricted dataset, and document the outcome Implement least-privilege access across datasets, reports, and dashboards What we’re looking for Must-haves Hands-on production experience with dbt (we run dbt Core) — this is a hard requirement Strong SQL expertise Solid Python for data engineering and automation Working knowledge of AWS data services Experience with GitHub and GitHub Actions (or equivalent CI/CD tooling) for testing and deploying data code Experience with a modern BI tool (e.g., Lightdash, Omni, Looker, or Metabase), and a genuine interest in semantic layers (e.g., MetricFlow, Cube Core) and self-serve analytics Comfortable using AI tools as part of your day-to-day engineering workflow Strong communication — you can sit with a non-technical stakeholder, understand their real problem, and explain trade-offs in plain language Ownership: you’re comfortable being the first and only person in this role, and building things properly from scratch Nice-to-haves Airflow or similar orchestration tools, and familiarity with data ingestion tools such as dlt or Airbyte Warehouse cost and performance tuning, particularly on Redshift Fintech, investment management, or another regulated industry Handling PII responsibly in an analytics environment — sanitised vs. restricted datasets, role-based access tiers, automated PII detection Experience with Notion AI or Asana automations Day-to-day working style We favour clear thinking and simple, well-tested solutions over cleverness We expect you to engage directly with the business, not hide behind tickets — understanding the “why” behind a request is part of the job We’re genuinely trying to use AI to work faster and better, not as a buzzword — we want people who’ll experiment, share what works, and level up the team As the first analytics engineer, you’ll define what “good” looks like here: process, standards, and tooling included We believe data should be as accessible as it can safely be, and as restricted as it needs to be — good judgement applied consistently, not blanket lockdown Practical details Reports to: Chief Data Officer Team: Data & Analytics Level: Mid to Senior Location / working pattern: London / hybrid