Данные и ML вакансии

Предстоит: Участвовать в планировании и запуске A/B-тестов, уметь интерпретировать результаты; Работать в связке с Data Scientist, Data Analyst: собирать требования, формировать и декомпозировать задачи, синхронизировать команду по статусам;

— Участвовать в управлении ML-продуктами: анализировать технические и продуктовые метрики, предлагать гипотезы, искать точки роста. — Участвовать в планировании и запуске A/B-тестов, уметь интерпретировать результаты.

• Уверенное знание SQL и Python. • Опыт работы с Apache Airflow.

разрабатывать и дообучать модели TTS: проектирование, finetuning и адаптация генеративных подходов для высококачественного синтеза речи и zero shot клонирования голоса под задачи бизнеса; участвовать в дальнейшей разработке голосового пайплайна, объединяющего ASR, VAD, LLM, NLP и TTS для работы в режиме реального времени;

Develop dbt data models, dashboards, metrics, and automation processes for the revenue field team and revenue analysts. Build and maintain critical reporting data models that power external merchant reporting.

Location: Remote About the Team: Netlify’s Data team helps the company understand and improve the full product-led growth journey, from activation and engagement through conversion, retention, and monetization. We partner closely with Product, Engineering, and Growth to uncover opportunities, evaluate investments, and understand what drives customer and business outcomes. We’re hiring a Senior Staff Data Scientist to deepen how data shapes our product and growth strategy. You’ll develop an end-to-end understanding of the PLG journey, proactively identify opportunities, and turn complex data into hypotheses, experiments, and recommendations that influence where we invest and what we build. This is a highly autonomous role for someone who can move from identifying an important question to shaping the approach, defining success, and driving toward an answer. What You'll Do: Own the analytical understanding of Netlify’s PLG performance across activation, engagement, conversion, monetization, and retention, identifying opportunities before they become requests Partner with Product and Engineering leadership to turn behavioral insights into product bets, defining what to test, how to measure it, and what the results mean Lead experimentation from hypothesis through decision, including study design, methodology, success metrics, guardrails, analysis, and recommendations Apply statistical rigor where it matters while recognizing when there is enough signal to make a decision and move forward, and help teams develop that same judgment Build scalable analytical systems like semantic models, trusted metrics, proactive monitoring, and AI-powered agents  that surface opportunities without waiting to be asked Use AI to investigate faster, automate recurring analytical work, and test more hypotheses without sacrificing the judgment that makes the output useful Identify gaps in measurement, event instrumentation, and metric definitions, and partner with Data and Product Engineering to close them Serve as a trusted analytical partner to PLG leadership, using evidence and product judgment to influence investment decisions and roadmap priorities Influence product strategy through evidence, product instincts, and a clear point of view, without relying on formal authority to do it What You'll Bring: 8+ years of experience in product analytics, growth analytics, or data science, with a track record of high ownership and measurable impact on PLG or consumer product outcomes Deep understanding of product and growth dynamics across activation, engagement, conversion, monetization, and retention Demonstrated ability to turn behavioral data into product hypotheses and carry them from insight through experimentation and measured outcomes Deep experimentation expertise: study design, statistical reasoning, causal inference, and the judgment to know when an experiment has told you what you need to know Experience building analytical systems such as metrics layers, monitoring frameworks, or semantic models that teams can rely on over time An AI-native approach to analysis: you use AI tools actively to accelerate investigation, automate repetitive work, and surface patterns faster A track record of influencing senior stakeholders and product direction through analytical reasoning, clear recommendations, and sound judgment Comfort operating with significant autonomy in ambiguous problem spaces, including determining which questions are most important to answer Strong written and verbal communication skills in distributed environments, with the ability to make complex findings clear and recommendations actionable This Role is a Great Fit If: You're energized by finding the opportunity before anyone thought to ask - proactive discovery is how you naturally work, not a mode you shift into You think like a product person who happens to be exceptionally rigorous with data, not a data person who occasionally weighs in on product You thrive when the problem isn't handed to you - you'd rather define the question worth asking than answer the one that landed in your queue You get excited about building systems that keep working after you've moved on to the next problem You're comfortable making a call with imperfect information and can articulate clearly why you made it You enjoy being a thought partner to senior leaders - shaping how they think about investment and opportunity, not just supporting decisions already made You work well in a remote-first, async environment where written clarity and self-direction matter more than proximity You're drawn to roles where the measure of success is outcomes, decisions made, bets tested, metrics moved, not volume of output produced Applying Not sure you meet 100% of our qualifications? Please apply anyway! When applying please include: A resume or short listing of your job history & skills (link to a LinkedIn profile would be fine). We appreciate a cover letter explaining why you would enjoy working in this role at Netlify to get to know you a bit better, though this is not required and will not impact your application. Our mission is to “build a better web” and that cannot be done without a diversity of skill sets, backgrounds and thoughts. Of everything we've ever built at Netlify, we are most proud of our team. Netlify is an Equal Opportunity Employer. We are devoted to building a team of people with diverse backgrounds and lifestyles. Driving equality empowers our team, enables us to innovate, and helps us maintain a more inclusive environment. We don’t discriminate against employees or applicants based on gender identity or expression, sexual orientation, religion, age, race, military/veteran status, citizenship, pregnancy status, or any other differences. If we can do anything to provide a better interview, i.e. accommodate a disability, then please let us know by emailing accommodations@netlify.com . About Netlify Netlify is the most popular way to build, deploy, and scale modern web applications, empowering everyone from fast moving solo developers to enterprise teams. Millions of developers and organizations rely on Netlify as their platform of choice for composing web applications that are production ready, performant, and flexible. Now, as we embrace the next era of software development, we are embedding the same fluid, intuitive experience into the Agent Experience (AX), making it just as simple for intelligent agents to understand, interact with, and act on our platform as it is for developers. Whether your user is human or machine, Netlify ensures the path from idea to URL is seamless, fast, and deeply reliable. We are a Series D company that has raised over $200M from investors such as Andreessen Horowitz, Kleiner Perkins, EQT, Bessemer, BOND, and Menlo Ventures. As a fully distributed company, we aim to create a company culture where the best idea can come from anywhere and strive to be thoughtful, compassionate, and collaborative in our work. If this sounds like something you’d like to be part of, we’re excited to connect with you! At Netlify, we are committed to a compensation philosophy that prioritizes fairness and equity, positions our employee compensation competitively in the market, recognizes and rewards performance, and takes a comprehensive approach to our rewards package. We anchor our compensation philosophy on a market-based approach, therefore salary ranges may differ depending on the labor cost in a particular location. The salary provided is in addition to robust benefits and participation in Netlify’s equity plan. Our hiring range for this role is targeted at $204,000 - $275,000 for most US-based locations.  Candidates outside the US or in premium markets should consult with their Talent Acquisition partner regarding location-based ranges, as they may be higher or lower than the average US range listed. The starting pay will be determined based on multiple factors, including expertise and skills, market demands, experience, internal equity, and applicable geographic location. These compensation packages and ranges are subject to change and may be modified in the future.

Миграция в целевую архитектуру данных. Реализация и систематизация ETL-процессов согласно требованиям.

Нужен опыт управления командой аналитиков, BI или Data от 3 лет и СИЛЬНАЯ ЭКСПЕРТИЗА В КОММЕРЧЕСКОЙ АНАЛИТИКЕ, ОСОБЕННО В ПРОДАЖАХ НА МАРКЕТПЛЕЙСАХ: АССОРТИМЕНТ, МАРЖИНАЛЬНОСТЬ, ЭФФЕКТИВНОСТЬ КАНАЛОВ И ДИНАМИКА ПРОДАЖ.

Location: Remote - US About the Job: AI-powered workflows are only as good as the customer data underneath them. LaunchDarkly helps engineering teams ship software faster and more safely through feature management, experimentation, and AI delivery tooling. As our GTM Data Governance Manager (MDM), you will  set the rules that make our core customer data (accounts, contacts, subscriptions, and users) accurate, consistent, and trusted across Salesforce, our billing and finance systems, marketing automation, product usage data, and the data warehouse. This is an individual contributor role with real ownership of the data model and its standards. You will partner with Data Engineering, GTM Systems, Finance Systems, Legal, and Security to put those standards into production. Your work is the foundation for reliable reporting, accurate territory and segmentation, clean pipeline attribution, and the AI workflows that depend on high-quality data. Responsibilities: Own the MDM roadmap and operating model for the account, contact, and organization hierarchy domains. Define golden record rules: matching, merging, survivorship, and parent/child hierarchies across CRM, billing, product, and support systems. Set data governance standards, including ownership, stewardship roles, definitions, and quality SLAs, in partnership with Sales, Marketing, Finance, and Customer Success. Run the processes for onboarding new data sources, handling change requests, and managing lifecycle events such as mergers, acquisitions, and customer reorganizations. Design and monitor data quality rules, scorecards, and dashboards covering completeness, accuracy, duplication, and timeliness. Drive remediation and report data health, risks, and progress to leadership with clear metrics and business impact. Specify integration patterns and acceptance criteria across Salesforce, the data warehouse, and enrichment providers, and work with Data Engineering and GTM Systems to build them. Recommend build vs. buy for MDM, identity resolution, enrichment, and data quality tooling. Provide trusted, well-documented data products for analytics and AI use cases. Act as the data owner with Legal and Security on PII handling, GDPR and CCPA requirements, retention, and access controls. Who You'll Work With: Data Engineering and GTM Systems build pipelines and Salesforce configuration. Legal and Security own privacy and security decisions, and you inform them as the data owner. You own the rules, standards, and acceptance criteria that tell everyone else what "correct" looks like. Qualifications: 8+ years of experience in data management, data governance, data engineering, or analytics, including 2+ years leading MDM or data quality programs. Hands-on experience designing match, merge, and survivorship rules and golden record or hierarchy models, with results you can describe. Experience with Salesforce data models and CRM data quality at scale. Experience building and operating a data governance framework: policies, stewardship models, and SLAs. Ability to translate business needs into data requirements and explain technical tradeoffs to non-technical stakeholders. A track record of delivering cross-functional programs without direct authority. Nice to Have Experience at a B2B SaaS company with a product-led or hybrid sales motion, including mapping product users and workspaces to CRM accounts. Familiarity with enrichment and firmographic data, entity matching approaches, and ML-assisted or LLM-assisted matching and cleansing. Working knowledge of data privacy regulations (GDPR, CCPA) and security frameworks such as SOC 2. Pay: Target pay ranges based on Geographic Zones* for Level 4: Zone 1: San Francisco/Bay Area or NYC Metropolitan Area, Boston, Seattle - $152,900 - $210,210 ** Zone 2: Irvine, LA, Monterey, Santa Barbara, Santa Rosa, Austin, Portland, Philadelphia, Chicago - $137,600 - $189,200 ** Zone 3: All other US locations - $129,900 - $178,640* * LaunchDarkly operates from a place of high trust and transparency; we are happy to state the pay range for our open roles to best align with your needs. Exact compensation may vary based on skills, experience, and location. *Within the United States, our geographic pay zones are defined by counties surrounding major metropolitan areas. **Restricted Stock Units (RSUs), health, vision, and dental insurance, and mental health benefits in addition to salary. About LaunchDarkly: Modern software delivery was supposed to be the foundation for a thriving digital business but reality has proven otherwise. Slow, inefficient development cycles, costly outages, and fragmented customer experiences are preventing developers from building their best software. The LaunchDarkly platform helps developers innovate on new features faster while protecting them with a safety valve to instantly rewind when things go wrong. Developers can target product experiences to any customer segment and maximize the business impact of every feature. And by gradually rolling out new application components, they escape nightmare "big-bang" technology migrations. The LaunchDarkly platform was built to guide engineers to the next frontier of DevOps by: Improving the velocity and stability of software releases, without the fear of end customer outages Delivering targeted experiences by easily personalizing features to customer cohorts Maximizing the business impact of every feature through the ability to experiment and optimize Coordinating the release and optimization of software to provide consistent experiences across mobile platforms and device types Improving the effectiveness and productivity of engineering teams, by providing insights into engineering cadence and stability At LaunchDarkly, we believe in the power of teams. We're building a team that is humble, open, collaborative, respectful and kind. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status. LD invites any applicant to review our written Affirmative Action Plan. To do so, contact People Ops at hr@launchdarkly.com . Do you need a disability accommodation? Fill out this accommodations request form and someone from our People Operations team will contact you for assistance. Your safety matters to us. To protect yourself from potential scams, LaunchDarkly recruiters will only contact you from @LaunchDarkly .com email addresses or via LinkedIn from "Verified Recruiter" accounts. Be cautious of emails from other domains.  Legitimate LaunchDarkly recruiters will never ask for money, fees, or banking information before making a job offer. LaunchDarkly will never make a job offer without conducting a formal interview process. Our interview process does not involve asking detailed questions by email. If you are ever unsure about a communication that you receive, don't click any links—visit Careers | LaunchDarkly directly for confirmed job openings and links to apply. Please notify us of any fraudulent representation by sending an email to careers@launchdarkly.com .

• Анализ требований: - Прием и анализ входящей документации от заказчиков.

Ваши обязанности: Разрабатывать и поддерживать ETL-процессы для загрузки данных в нашу DWH на Vertica; Проектировать и развивать витрины данных, чтобы аналитики и бизнес-пользователи получали точные и своевременные метрики;

Роль предполагает разработку и внедрение моделей машинного обучения, анализ данных, решение бизнес-задач с помощью ML и взаимодействие с командой для создания и улучшения интеллектуальных решений.

-Проводить исследовательский анализ данных блокчейн сети, включая транзакции, смарт-контракты и адреса. -Идентифицировать аномалии и анализировать их причины.

Задачи: — Руководство командой дата-инженеров (распределение задач, декомпозиция) — Выстраивание рабочих процессов и технологических стандартов — Проектирование и развитие архитектуры обработки и хранения данных — Организация сбора и обработки данных для продуктовых команд и аналитиков — Обеспечение качества и своевременной доставки данных — Поддержка BI-команды в задачах, связанных с данными Требования: — Опыт в Data Engineering от 5 лет — Опыт руководства командой либо замещения руководителя — Навыки проектирования хранилищ данных и пайплайнов обработки — Широкий технический кругозор в инструментах работы с данными — Умение выстраивать процессы и взаимодействовать со смежными командами — Продуктовый подход к работе с данными

Location: United States of America Why Join Exadel We’re an AI-first global tech company with 25+ years of engineering leadership, 2,000+ team members, and 500+ active projects powering Fortune 500 clients, including HBO, Microsoft, Google, and Starbucks. From AI platforms to digital transformation, we partner with enterprise leaders to build what’s next. What powers it all? Our people are ambitious, collaborative, and constantly evolving. About the Client A global technology leader specializing in search technology, digital advertising, cloud computing, and artificial intelligence. Delivering enterprise cloud infrastructure and software solutions, the organization builds scalable consumer and enterprise AI experiences. Today, the company leverages foundational AI models and advanced machine learning to power digital ecosystems for billions of global users. What You’ll Do Conduct formal, end-to-end written privacy reviews for products, features, research publications, data pipelines, and experimental prototypes Evaluate privacy risks and recommend practical safeguards aligned with internal standards and applicable global regulations Manage reviews from initial discovery and risk identification through remediation and final approval Provide strategic guidance and support the escalation of complex or high-risk privacy matters Maintain accurate, detailed, and audit-ready assessment documentation Assess the privacy implications of AI, machine learning, generative AI, and Large Language Model systems Evaluate data ingestion, prompt inputs, context windows, model outputs, training workflows, inference processes, and human-in-the-loop oversight Identify potential risks involving personal data, data leakage, memorization, secondary use, data retention, and inappropriate model outputs Recommend appropriate privacy controls for experimental and production AI systems Support the responsible development and launch of emerging AI capabilities Review technical design documents, Product Requirements Documents, Business Requirements Documents, system architecture diagrams, data-lineage documentation, and academic publications Identify privacy touchpoints, data dependencies, and potential gaps across product and data-processing lifecycles Translate privacy, legal, and compliance requirements into practical and actionable guidance for product and engineering teams Evaluate complex product scenarios in which requirements, risks, or ownership may not yet be clearly defined Partner with product managers, software engineers, data scientists, legal teams, and privacy stakeholders to incorporate privacy controls throughout the product lifecycle Evaluate controls relating to notice and consent, transparency, user choice, data portability, data minimization, access, and retention Review data-collection practices, consent flows, access controls, privacy policies, and user-facing privacy notices Help teams make informed product decisions that balance innovation, regulatory obligations, and user trust Identify gaps in existing privacy-review processes and recommend operational improvements Develop and refine privacy frameworks, standard operating procedures, guidelines, templates, and review criteria Support operational reporting and program-management activities across the privacy lifecycle Use custom tools and AI technologies to automate workflows, improve review efficiency, and optimize governance operations Help establish consistent and scalable privacy-review practices across research and innovation teams What You Bring Extensive hands-on experience conducting formal written privacy reviews, assessments, or impact analyses Product-focused privacy experience within technology, digital platforms, cloud services, AI, or similarly complex environments An active IAPP certification in at least one of the following: Artificial Intelligence Governance Professional, Certified Information Privacy Professional/United States, Certified Information Privacy Professional/Europe, Certified Information Privacy Manager Practical knowledge of AI and machine learning data-processing workflows, generative AI applications, and Large Language Models Understanding of privacy risks associated with model-training data, user inputs, inference processes, and model outputs Deep knowledge of privacy principles, including notice and consent, transparency, user choice, data portability, data minimization, and retention Knowledge of relevant privacy and AI regulatory frameworks, including GDPR, CCPA, and the EU AI Act Ability to interpret complex software-design documents, system architectures, data flows, and product requirements Experience managing multiple reviews and competing priorities under tight deadlines Strong judgment and the ability to make well-supported recommendations in ambiguous or rapidly evolving environments Exceptional written and verbal English communication skills Ability to translate legal and compliance requirements into clear, actionable technical guidance Strong stakeholder-management and influencing skills across product, engineering, legal, and governance teams Nice to have Familiarity with enterprise privacy-review, governance, and product-launch tools Experience supporting privacy governance for research, experimental products, or emerging technologies Experience working with cross-functional legal, ethics, privacy, product, and engineering governance bodies Experience automating privacy-review or governance workflows using AI or custom tooling A degree in Law, Computer Science, Data Governance, Information Security, or a related discipline Additional privacy, security, risk, or AI-governance certifications English level Advanced Work Type: Remote Location: United States Working Hours: Alignment with west coast US time zone Legal & Hiring Information Compensation Transparency: The expected compensation range for this role is $50–100/hr USD, with eligibility for commission, bonus, or other incentive compensation where applicable. Actual compensation will be determined based on experience, skills, qualifications, geographic location within the United States, and business needs. Location Eligibility: This role is open to candidates residing in the United States. Experience Requirements: We welcome applicants with relevant experience regardless of where it was obtained. US work experience is not required. Use of Artificial Intelligence in Hiring: We may use automated tools or artificial intelligence systems to support the screening, assessment, or selection of applicants as part of our hiring process. Benefits Summary: US-based employees are eligible to participate in Exadel’s benefits programs, which may include comprehensive health, dental, and vision coverage; life and disability insurance; retirement savings programs; paid time off; paid holidays; and other wellness or voluntary benefit programs, subject to plan terms and eligibility requirements. Equal Employment Opportunity: Exadel is proud to be an Equal Opportunity Employer committed to inclusion across minority, gender identity, sexual orientation, disability, age, and more. We do not discriminate on the basis of race, color, religion, sex, gender identity or expression, sexual orientation, national origin, age, disability, status as a protected veteran, or any other protected characteristic under applicable federal, state, and local laws. Accessibility and Accommodation: We are committed to providing accommodations throughout the recruitment process in accordance with the Americans with Disabilities Act (ADA) and other applicable federal, state, and local accessibility laws. Reasonable accommodations are available to enable individuals with disabilities to perform essential functions. If you require accommodation at any stage of the hiring process, please contact us. Data Privacy Notice: For applicants residing in California, please note that personal data collected during the application process is subject to the California Consumer Privacy Act (CCPA) and will be processed in accordance with our applicant privacy notice. Disclaimer: Please note: this job description is not exhaustive. Duties and responsibilities may evolve based on business needs. The offer is not binding until a signed contract is in place. Exadel Culture We lead with trust, respect, and purpose. We believe in open dialogue, creative freedom, and mentorship that helps you grow, lead, and make a real difference. Ours is a culture where ideas are challenged, voices are heard, and your impact matters.

Мы приглашаем в нашу команду опытного ML инженера для работы над проектом по созданию системы анализа данных.

— кандидатов с опытом работы от 3,5 лет в крупных российских и международных IT-, BigTech- и FinTech-компаниях. — с опытом полного цикла разработки моделей: от ресёрча до выкатки в продакшен.

• Разработка кросс-ассетных стратегий: Поиск альфа-сигналов, построение и валидация математических и ML-моде...