Данные и ML вакансии

Creating new and improving existing AI solutions Involvement in the whole process of data-driven development from analyzing product requirements to launching the feature or system to production (with the help of MLOps specialists) and improving it based on results of monitoring and feedback.

— Разрабатывает модули планирования снабжения и производства. — Проектирует и реализует компоненты для календарного и производственного планирования и оптимизации запасов.

Проводить исследования на основе большого количества реальных гитарных джемов. Работать с существующими open source моделями и трансформировать их под музыкальные задачи.

Location: Remote - US Workplace: Remote ABOUT US At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developers move from prototypes to production-ready AI agents that teams can rely on. We began as widely adopted open-source tools and have grown to also offer a platform for building, evaluating, deploying, and operating agents at scale. With $125M raised at Series B from IVP, Sequoia, Benchmark, CapitalG, and Sapphire Ventures, we’re at a stage where we’re continuing to develop new products, growth is accelerating, and all team members have meaningful impact on what we build and how we work together. LangChain is a place where your contributions can shape how this technology shows up in the real world. Today, our platform includes LangSmith (Observability, Evaluation, Deployment, Fleet, and Sandboxes), our open source frameworks (LangChain, LangGraph, and Deep Agents), and the newly launched LangSmith Engine for autonomous agent improvement. We have 100M+ monthly open source downloads, 6,000+ active LangSmith customers, and 5 of the Fortune 10 use LangSmith in production (+ 35% of the Fortune 500 overall), including teams at Klarna, Clay, Coinbase, Workday, Lyft, Cloudflare, Harvey, Rippling, Vanta, LinkedIn, Monday.com, Nvidia, and Bridgewater. ABOUT THE TEAM: We are a small but mighty team of three analytics engineers powering LangChain’s internal data infrastructure and analytics. We’re a full-stack team, meaning we work end-to-end across the data stack, from data ingestion to enabling self-serve agentic analytics. Learn more about what we’ve built so far here https://www.langchain.com/blog/agent-data-stack! ABOUT THE ROLE: We are expanding our data team and looking for a analytics engineer to join us. We build products used by elite companies and over a million developers, and data plays a critical role in sharping our strategies and decision making. In this role you will help lay the foundation for business teams to diagnose issues, uncover opportunities, and drive success using data. If you enjoy building data infrastructure and empowering teams with actionable insights, this role is for you. *Location: SF, NYC, Boston, or Remote U.S. WHAT YOU WILL DO: - Build scaleable dbt models and context that describe our business, powering a self-serve analytics experience - Work with and expand on our foundational data stack — Fivetran, dbt, BigQuery, Hex - Connect data from a variety of sources (Salesforce, Stripe, Metronome, Postgres, etc) into our BigQuery warehouse - Build dashboards that track progress against company goals and KPIs - Analyze product usage and operational data to surface insights around customer health, adoption, and revenue - Develop and leverage a deep understanding of our business metrics to drive alignment and decision-making WHAT YOU'LL BRING: - 3+ years experience in a related role (analytics engineer, data engineer, or similar) - Technical proficiency in BigQuery, dbt, Hex, Fivetran, Segment (or similar tools) - Detail oriented, enjoys data spelunking, and can synthesize findings effectively - Curiosity and a strong business sense to help anticipate needs and generate meaningful insights - Start up DNA. You thrive in fast-paced and unstructured environments and are energized by finding out what matters most - You are self-directed - you don’t wait for process or oversight to start making an impact Compensation & Benefits: We offer competitive compensation that includes base salary, meaningful equity, and benefits such as health and dental coverage, flexible vacation, a 401(k) plan, and life insurance. Actual compensation will vary based on role, level, and location. For team members in the EU and UK, we provide locally competitive benefits aligned with regional norms and regulations. Annual salary range: $140,000-$180,000 Compensation Philosophy: We offer competitive compensation that includes base salary, variable compensation for relevant roles, meaningful equity, benefits, and perks. We are hiring for this role across a range of scope, and the compensation band reflects that. Your offer depends on what we learn about your impact, craft, leadership, and communication during the interview process. We will tell you early where you’re tracking and talk comp with you before offer stage. Team members in the EU, UK, and APAC receive locally competitive benefits aligned with regional norms and regulations. BENEFITS Benefits include medical, dental, and vision coverage, flexible vacation, a 401(k) plan, meals on in-office days in the US and more.

-управлять командой, состоящей из DS, DE, MLOps. -соблюдать требования и стандарты производственного процесса банка.

Location: Berlin, Germany; Helsinki, Finland; London, United Kingdom About Wolt At Wolt, we create technology that brings joy, simplicity and earnings to the neighborhoods of the world. In 2014 we started with delivery of restaurant food. Now we’re building the delivery of (almost) everything and you’ll find us in over 500 cities in 30 countries around the world. In 2022 we joined forces with DoorDash and together we keep on dreaming big and expanding across the globe. Working at Wolt isn’t always easy, but it’s definitely exciting. Here you’ll learn more, build more, and ship more than in most other companies. You’ll be challenged a lot, but also have a lot of fun on the way. So, if you’re a self-starter with drive and entrepreneurial spirit, this could be the ride of your life. We are looking for an experienced Data Analytics Engineer to join our growing Tax Data Mart team. This role will be a key contributor to the team and will be responsible for building the tax data operations function for our Deliveroo and Wolt legal entities.  This includes building and operating the data pipelines and infrastructure that power tax analytics and support decision-making across the company. As DoorDash continues to grow its global footprint across multiple business lines, we are looking for a candidate with experience working with Tax teams to gather requirements, and designing scalable data processes to support them.. This person will grow our unique community via your blend of tax, data technology, and process improvement experience. About the Role You will be reporting to the Senior Manager of Tax Data & Operations, and play an integral role in DoorDash’s data function, owning the processes for ingesting, transforming, and controlling our data, ensuring accuracy, and making it available to analytics and business users. As a member of this team, you will lead the design, implementation, and operation of data pipelines and related processes to support the Company’s exponential growth. What you’ll be doing Lead the collection of Tax Data and Reporting requirements through close relationships with Tax team counterparts Design, build, and maintain scalable, reliable data pipelines (ETL/ELT) that serve data across the company Develop and optimize data models and warehouse structures to support analytics and reporting Participate in new business initiatives and identify their impact on existing data system(s) and processes. Work closely with Analytics, Data Science, and business partners in the development and validation of new data sources. Identify and document business, functional and technical requirements to support new business initiatives and to enhance existing system functionality. Leverage AI & AI assisted tooling to build and automate recurring data tasks & pipelines. Monitor data quality, reliability, and observability, and resolve data-related issues for our internal business partners. Participate in defining the Company’s data tooling needs, including the maintenance of existing systems. Prepare documentation related to our data systems and processes. Share knowledge and best practices with engineers and analysts across the team. Our humble expectations You have 7+ years of experience in a Tax data & technology or similar role. Experience using Data Build Tool (DBT) or a similar product to manage data flows. Experience using Claude, Cursor and similar AI tools. You are an expert at using SQL with experience using Snowflake. Proficiency in Python (or a comparable language) for building data pipelines. Experience with modern data stack and orchestration tools such as Airflow, Spark, or Kafka. You have strong attention to detail and analytical, organizational, and problem-solving skills. You’re an independently motivated person with a proven ability to manage multiple projects and prioritize work independently. You have excellent written and verbal communication skills. Project management experience, including creation of project plans, milestones, and due dates. Computer Science, Information Technology, Engineering, or a related degree. Our Commitment to Diversity and Inclusion We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of people from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. Beware of recruitment scams: DoorDash, Deliveroo, and Wolt will never ask you to pay money or share sensitive financial information during hiring — learn more about our legitimate recruiting process at Recruitment Scam Awareness - DoorDash .

Задачи: — Управление Cost of Risk по всем кредитным продуктам. — Создание и развитие моделей скоринга, поведенческого анализа и кредитных лимитов — от гипотезы до внедрения в продакшен. — Автоматизация программы повышения кредитного лимита с переходом от ручных правил к машинному обучению. — Контроль процессов взыскания на ранних и поздних стадиях, включая восстановление задолженности. — Разработка методологии резервирования совместно с финансовым отделом. — Подготовка ежемесячных отчетов по рискам для CEO и совета директоров. — Установление стандартов валидации моделей, мониторинга и регулярного переобучения. Требования: — Опыт работы 6+ лет в области кредитного риска по необеспеченным потребительским кредитам, включая 2+ года на руководящей должности. — Практический опыт создания моделей скоринга, поведенческого анализа и кредитных лимитов. — Прямое управление показателем Cost of Risk / NPL как ключевым метрикой эффективности. — Глубокое понимание процессов взыскания как части общей кредитной экономики. — Опыт работы с распределенными командами. — Профессиональный уровень английского языка. — Русский язык является плюсом. Желательно: — Опыт работы с картовыми программами и автоматизированным управлением кредитными лимитами. — Опыт работы с BNPL / рассрочкой. — Опыт внедрения ML-моделей в продакшен. — Опыт работы в регулируемом банке. — Опыт работы в Латинской Америке и знание испанского языка.

Location: Moldova Company Background Coherent Solutions is a global digital product engineering company founded in 1995 and headquartered in Minneapolis, Minnesota. With a presence in nine countries and a team of more than 1,700 engineers, the company provides custom software development and engineering services across web and mobile applications, cloud, DevOps, and data. Coherent Solutions works with clients worldwide to build and scale digital products while fostering a culture of collaboration, transparency, and continuous professional growth. Project Description You will work with senior engineers on internal classical machine learning initiatives. The role combines structured learning, practical delivery, and gradual ownership of increasingly complex tasks. Technologies Python, pandas, NumPy, scikit-learn, Jupyter SQL XGBoost, LightGBM MLflow FastAPI Git, Docker, pytest What You'll Do Prepare and validate structured datasets for machine learning tasks, including cleaning, transformation, encoding, scaling, and missing-value handling; Conduct exploratory data analysis to identify patterns, data quality issues, and opportunities for modeling; Build, test, and compare ML models for tasks such as regression, classification, clustering, dimensionality reduction, and anomaly detection; Develop and select features with guidance from senior engineers; Run experiments, tune model parameters, and evaluate results using appropriate validation approaches and metrics; Help maintain reproducible ML pipelines, notebooks, experiment tracking, and technical documentation; Write and maintain automated tests for data and model-related code; Support the delivery of models through REST APIs or batch-processing workflows; Document model assumptions, results, limitations, and technical decisions; Work closely with senior engineers, incorporate feedback, and gradually take ownership of more complex tasks; Job Requirements 1+ year of hands-on Python development experience, including experience with pandas, NumPy, scikit-learn, and Jupyter; A strong foundation in statistics, probability, and linear algebra, plus exploratory data analysis skills; An understanding of supervised and unsupervised learning, and practical experience with regression, classification, clustering, dimensionality reduction, and anomaly detection; Experience preparing structured datasets, including cleaning, transformation, encoding, scaling, and missing-value handling, plus practical feature engineering and feature-selection skills; An understanding of train/validation/test splits, cross-validation, data leakage, overfitting, and regularization; the ability to select appropriate evaluation metrics, compare models, and perform error analysis; Familiarity with hyperparameter tuning and reproducible ML pipelines; SQL skills for data extraction and analysis; The ability to expose models through REST APIs or batch-processing workflows; Familiarity with Git, automated testing, Docker, and basic model monitoring; The ability to explain model behavior, assumptions, limitations, and results; English at B2 level or higher; Nice To Have XGBoost, time-series analysis, recommendation systems, MLflow, model interpretability, cloud services, production ML monitoring, and GenAI, LLM, RAG, prompt-engineering, or agent-development experience; What Do We Offer The global benefits package includes: Technical and non-technical training for professional and personal growth; Internal conferences and meetups to learn from industry experts; Support and mentorship from an experienced employee to help you professional grow and development; Health insurance; Sports activities to promote a healthy lifestyle; Flexible work options, including remote and hybrid opportunities; Referral program for bringing in new talent; Work anniversary program and additional vacation days.

Ищем инженера с практическим опытом работы с геопространственными данными, дорожными графами и/или алгоритмами маршрутизации. - Разработка и оптимизация алгоритмов маршрутизации и построения маршрутов (VRP, TSP, роутинг с ограничениями по времени / весу / зонам);

-Исследовать большие объемы данных о покупательском поведении и находить закономерности для решения бизнес-задач. -Разрабатывать и улучшать ML-модели для прогнозирования оттока и отклика пользователей.

- Миграция ETL-системы телеком-оператора с Oracle/Informatica на Apache стек (S3, Airflow, NiFi, Kafka, Greenplum); - Перенос бизнес-логики из Informatica в высокопроизводительный SQL-код;

– Разработка, создание и оптимизация масштабируемых ETL-процессов и конвейеров обработки данных. – Разработка и поддержка решений в области бизнес-аналитики, хранилищ данных и аналитических наборов данных.

Создавать систему эффективного хранения больших данных и доступа к ним для ML-разработчиков. • Майнинг данных.

Location: Pune, India Workplace: Hybrid Solvd Inc. is a rapidly growing AI-native consulting and technology services firm delivering enterprise transformation across cloud, data, software engineering, and artificial intelligence. We work with industry-leading organizations to design, build, and operationalize technology solutions that drive measurable business outcomes. Following the acquisition of Tooploox, a premier AI and product development company, Solvd now offers true end-to-end delivery—from strategic advisory and solution design to custom AI development and enterprise-scale implementation. Our capability centers combine deep technical expertise, proven delivery methodologies, and sector-specific knowledge to address complex business challenges quickly and effectively. We are looking for a Senior Data Engineer to join a team migrating a production SaaS data platform off a legacy ETL/streaming-based pipeline and onto a Snowflake Native Application built for self-serve distribution and per-tenant data isolation. This isn't a greenfield build — it's a migration with real legacy constraints. You'll be working from an existing production system that has already been audited in detail, and turning those findings into a working Snowflake-native data platform. You should be comfortable reading someone else's architecture, spotting where it breaks down at scale or under multi-tenant isolation requirements, and redesigning around it. WHAT YOU'LL DO - Re-architect ingestion — design and build the replacement for the current endpoint-to-cloud-function-to-streaming-queue-to-ETL-to-warehouse path, moving ingestion natively into each customer's own Snowflake account so the platform's data-sovereignty story is true end to end. - Migrate legacy ETL logic — translate existing transformation logic covering activity, meeting/event, network context, and system metadata data into Snowflake-native pipelines using the right combination of native transformation tooling and orchestration. - Design for per-tenant isolation — build data models and pipeline logic that hold up under a cross-account, multi-tenant distribution model, with tenant boundaries addressed explicitly at the schema, pipeline, and secret-management level. - Work through known technical debt — shared credentials baked into client-side builds, build-time-only configuration with no live tenant provisioning, inconsistent cross-platform data-capture parity — deciding case by case what gets carried forward, redesigned, or retired. - Rebuild the platform's core data model — activity, event, network, and metadata — preserving the analytics the business depends on while moving underlying storage and processing into Snowflake. - Validate against real production data patterns — batch sizes, sync frequencies, offline-queue backlogs — captured during discovery to ensure the new pipeline design holds up under realistic load. - Document migration decisions clearly enough to be defended internally, to downstream customers, and through a formal marketplace review process. REQUIRED SKILLS & EXPERIENCE - 5+ years as a data engineer with hands-on Snowflake experience — native transformation and orchestration features, not just SQL. - Real experience migrating an existing production ETL pipeline to a cloud-native target — not a from-scratch build. - Working knowledge of streaming and event pipelines. - Comfortable reading and reasoning about a system's security model — encryption at rest and in transit, key management, multi-tenant secret handling — well enough to flag when a proposed design reintroduces a previously identified gap. - Familiarity with a major cloud provider's function/PaaS services, as parts of the migration will need to interoperate with the current production system during transition. - Experience designing for multi-tenant SaaS data isolation — schema-per-tenant, row-level security, or equivalent patterns. PREFERRED QUALIFICATIONS - Experience building and distributing applications through a cloud data platform's own marketplace or listing model. - Background in workforce analytics, activity monitoring, or similar behavioral/event data domains — application/window/URL activity, meeting data, network context. - Exposure to BI tooling migration alongside an underlying data platform move. When you join Solvd, you'll… - Shape real-world AI-driven projects across key industries, working with clients from startup innovation to enterprise transformation. - Be part of a global team with equal opportunities for collaboration across continents and cultures. - Thrive in an inclusive environment that prioritizes continuous learning, innovation, and ethical AI standards. Ready to make an impact? If you're excited to build things that matter, champion responsible AI, and grow with some of the industry’s sharpest minds. Apply today and let’s innovate together. Solvd is an equal opportunity employer.

Вам предстоит дополнить фундаментальный анализ количественным: собрать данные, построить модели и инструменты, на которые будут опираться инвестиционные решения. • Мониторинг: создать систему, которая регулярно сверяет инвест тезисы с новыми данными и показывает подтверждается тезис, слабеет или требует пересмотра.

💼 Role: Data Scientist.

• Техническое развитие направления. Вы будете формировать технический курс, выбирать ключевые гипотезы и принимать решения по результатам экспериментов.

-Разработка и обучение моделей для анализа изображений и облаков точек. -Подготовка датасетов, анализ данных.