Данные и ML вакансии

Задачи: — сбор данных на татарском языке для AI/LLM Требования: — свободное владение татарским языком (родной или уровень носителя) — внимательность, усидчивость, способность работать по инструкции — базовые навыки работы с компьютером или смартфоном (для записи аудио) — опыт работы не требуется, всему научат Условия: — полная занятость — график 6/1 или 5/2 — удалённый формат работы — зарплата от 38 000 ₽ за месяц на руки

-реализовывать высоконагруженные конвейеры обработки данных для обеспечения надежной и бесперебойной репликации данных из ИТ-систем. -реализовывать комплексные задачи по подготовке данных в целевых аналитических хранилищах (DataLake, SandBox, FeatureStore) для построения признаков, необходимых для разработки моделей машинного обучения.

Разрабатывать и исследовать ML-модели для генерации изображений и визуализации интерьерных/строительных решений на основе товаров Лемана ПРО. Проектировать и реализовывать end-to-end пайплайны для PoC: от сбора и подготовки данных до обучения, оценки и демонстрации результатов.

Тебе предстоит решать исследовательские и прикладные задачи: от анализа данных и разработки метрик до создания, внедрения и сопровождения алгоритмов. Чем предстоит заниматься Анализировать и обрабатывать данные различного объёма и структуры.

— Разрабатывать и поддерживать реализованные рекомендательные решения. — Искать новые гипотезы для улучшения пайплайнов обучения моделей и добавления новых признаков.

Location: United States Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.   We’re looking for a Senior Analytics Engineer to join Kraken’s Finance Data Eng & Analytics team within Data Platform. You’ll build trusted financial data products, using automation and AI to reduce manual work and improve the close process. Working at the intersection of data engineering and accounting, you’ll turn complex financial data into reliable pipelines, models and automated reconciliations. You’ll use AI-assisted tools to accelerate development and investigations, keeping financial outputs tested and traceable.   THE OPPORTUNITY - You’ll work closely with Data Engineers, Finance and Platform Accounting to improve reporting and decision-making. Clear communication and collaboration will help you agree priorities, explain findings and drive adoption. - Partner with Finance to understand workflows, identify pain points and translate business needs into practical data and automation solutions. - Build and maintain automated workflows for data preparation, reconciliations, reporting and follow-ups, with clear controls, monitoring and exception handling. - Build intuitive dashboards and visualizations that help stakeholders understand performance, investigate issues and make decisions. - Resolve finance data issues and reconciliation breaks with Finance, Product and Engineering, addressing root causes and communicating progress. - Build scalable, reliable pipelines to collect, transform and curate data from internal platforms and external systems. - Support the design and rollout of a trusted finance data lake, with clear definitions, ownership and quality checks. - Improve data timeliness, enabling near-real-time insights where they add business value. - Evaluate new technologies, including AI-assisted automation, and prototype solutions to Finance needs that can be reliably supported in production.   WHAT YOU BRING - 7+ years of experience in data analytics and data management within financial services or a regulated industry, working directly with Finance teams. - Strong SQL and Python skills, including writing, debugging and maintaining production code. - Solid experience with Git, merge requests, and code reviews, supported by strong software engineering practices, including testing and documentation. - Hands-on experience building and operating pipelines and models using dbt, Spark, Airflow or comparable tools. - Direct experience with finance or accounting data, such as reconciliations, subledgers, cost basis or month-end close, including investigating discrepancies and validating outputs with accounting stakeholders. - A track record of owning pipelines end to end, making sound technical decisions and improving reliability as requirements and systems evolve. - Judgment and autonomy to lead complex work, navigate ambiguity and remain accountable for production outcomes. - Experience supporting recurring financial close activities, combined with a proactive approach to identifying manual processes and replacing them with reliable, sustainable automation. - Excellent communication skills, with the ability to collaborate across Engineering and Finance, explain complex technical issues, articulate financial implications, and recommend actionable solutions.   NICE TO HAVES - Experience with cryptocurrency transaction data and how digital-asset activity flows into financial records and reconciliations. - Experience processing large volumes of financial transactions using distributed frameworks such as Spark or PySpark. Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

Location: Brazil; Peru; Colombia; Argentina; Canada; Mexico; Chile Workplace: Remote BUILDING THE FUTURE OF OPEN FINANCE Payward - the parent company behind Kraken, NinjaTrader, Breakout, xStocks, Payward Services and CF Benchmarks - has spent the last 15 years building one of the most modern and globally accessible financial infrastructure platforms in the industry, built to advance an open, global financial system. THE TEAM Founded in 2011, Kraken is one of the world's longest-standing crypto platforms, trusted by over 10 million individuals and institutions across the globe. It offers spot trading, margin, futures, staking, and OTC services, with products built for both individual investors and institutional clients.   We’re looking for a Senior Analytics Engineer to join Kraken’s Finance Data Eng & Analytics team within Data Platform. You’ll build trusted financial data products, using automation and AI to reduce manual work and improve the close process. Working at the intersection of data engineering and accounting, you’ll turn complex financial data into reliable pipelines, models and automated reconciliations. You’ll use AI-assisted tools to accelerate development and investigations, keeping financial outputs tested and traceable.   THE OPPORTUNITY - You’ll work closely with Data Engineers, Finance and Platform Accounting to improve reporting and decision-making. Clear communication and collaboration will help you agree priorities, explain findings and drive adoption. - Partner with Finance to understand workflows, identify pain points and translate business needs into practical data and automation solutions. - Build and maintain automated workflows for data preparation, reconciliations, reporting and follow-ups, with clear controls, monitoring and exception handling. - Build intuitive dashboards and visualizations that help stakeholders understand performance, investigate issues and make decisions. - Resolve finance data issues and reconciliation breaks with Finance, Product and Engineering, addressing root causes and communicating progress. - Build scalable, reliable pipelines to collect, transform and curate data from internal platforms and external systems. - Support the design and rollout of a trusted finance data lake, with clear definitions, ownership and quality checks. - Improve data timeliness, enabling near-real-time insights where they add business value. - Evaluate new technologies, including AI-assisted automation, and prototype solutions to Finance needs that can be reliably supported in production.   WHAT YOU BRING - 7+ years of experience in data analytics and data management within financial services or a regulated industry, working directly with Finance teams. - Strong SQL and Python skills, including writing, debugging and maintaining production code. - Solid experience with Git, merge requests, and code reviews, supported by strong software engineering practices, including testing and documentation. - Hands-on experience building and operating pipelines and models using dbt, Spark, Airflow or comparable tools. - Direct experience with finance or accounting data, such as reconciliations, subledgers, cost basis or month-end close, including investigating discrepancies and validating outputs with accounting stakeholders. - A track record of owning pipelines end to end, making sound technical decisions and improving reliability as requirements and systems evolve. - Judgment and autonomy to lead complex work, navigate ambiguity and remain accountable for production outcomes. - Experience supporting recurring financial close activities, combined with a proactive approach to identifying manual processes and replacing them with reliable, sustainable automation. - Excellent communication skills, with the ability to collaborate across Engineering and Finance, explain complex technical issues, articulate financial implications, and recommend actionable solutions.   NICE TO HAVES - Experience with cryptocurrency transaction data and how digital-asset activity flows into financial records and reconciliations. - Experience processing large volumes of financial transactions using distributed frameworks such as Spark or PySpark.       Unless a specific application deadline is stated in the job posting, applications are accepted on an ongoing basis. Please note, applicants are permitted to redact or remove information on their resume that identifies age, date of birth, or dates of attendance at or graduation from an educational institution. We consider qualified applicants with criminal histories for employment on our team, assessing candidates in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance. OUR COMMITMENT Payward is powered by people from around the world and we celebrate the diverse talents, backgrounds, contributions, and unique perspectives that everyone brings to the table. We hire based on merit, seeking out people with the right abilities, knowledge, and skills for the job. We encourage you to apply for roles where you don't fully meet the listed requirements, especially if you're passionate or knowledgeable about crypto. We may ask candidates to complete job-related skills or work-style assessments as part of our hiring process. These assessments evaluate competencies relevant to the role and are applied consistently across candidates for similar positions. Results are considered alongside experience and interviews, and are not the sole basis for any employment decision. As an equal opportunity employer, we don't tolerate discrimination or harassment of any kind, whether based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status, or any other protected characteristic as outlined by federal, state, or local laws. Stay connected Follow us on Twitter https://twitter.com/krakenfx Learn on the Kraken Blog https://blog.kraken.com/#:~:text=Enter%20your%20email%20address Connect on LinkedIn https://www.linkedin.com/company/kraken-exchange/ Candidate Privacy Notice https://www.kraken.com/legal/candidate-privacy-notice

- 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;

- Сильный опыт в ML, Deep Learning, NLP и LLM. - Практический опыт создания AI-продуктов, работающих в production и в большом масштабе.

- 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;

• 8+ лет опыта в прикладном ML/AI с ответственностью за системы end-to-end. • Уверенное владение Python.

· Разработка и совершенствование моделей: Проектирование,. оценка и постоянное улучшение прогнозных моделей для выявления рисков,.

Исследовать и сравнивать подходы к решению прикладных задач: от классического ML до LLM-пайплайнов. Строить и валидировать модели: классификация, NER, matching, извлечение и нормализация данных, ranking, генерация.

Руководить командой Data Science: развивать экспертизу, выстраивать процессы, помогать сотрудникам расти и достигать результата. От 10 лет опыта в Data Science.

решать продуктовые задачи с помощью ML: от постановки гипотезы и исследования данных до запуска решения в production и оценки бизнес-эффекта; развивать ML-модели, влияющие на клиентский опыт и бизнес-метрики продукта.

-Улучшать текущие и разработка новых моделей для рекомендаций. -Исследовать современные подходы.

Модели продаж: строить и улучшать маркетинг-микс модели продаж брендов.

Задачи: — участвовать в полном цикле разработки AI-агентов и универсальных ассистентов: от идеи и проектирования до запуска в продакшн — проводить эксперименты, тестировать гипотезы и исследовать новые подходы для создания агентских решений — разрабатывать и внедрять LLM-пайплайны, чат-ботов и интеллектуальные системы — обучать и дообучать NLP-модели под конкретные задачи продукта — интегрировать разработанные модели и логику в бизнес-процессы — мониторить качество работы моделей в продакшне, находить узкие места и оперативно вносить улучшения. Требования: — опыт в NLP и понимание технологий: от классических алгоритмов до трансформеров и генеративных моделей (LLM) — практический опыт коммерческой разработки AI-агентов, чат-ботов и LLM-пайплайнов — опыт обучения глубоких нейронных сетей — уверенное владение PyTorch, NumPy, Pandas, а также фреймворками для работы с агентами: LangChain, LangGraph (или их аналогами) — уверенное владение Python, Git, SQL, Bash, Docker. Умение писать чистый, поддерживаемый и тестируемый код — навык перевода бизнес-требований в конкретные технические и алгоритмические решения. Будет плюсом: — понимание принципов микросервисной архитектуры и опыт проектирования REST API — опыт разработки асинхронных и многопоточных приложений (asyncio, aiohttp, multiprocessing и др.) — опыт взаимодействия с реляционными и нереляционными базами данных — практический опыт настройки и поддержки CI/CD-пайплайнов (Jenkins, GitLab CI, ArgoCD или аналоги) — опыт развёртывания и управления приложениями в Kubernetes. Условия: — комфортный современный офис рядом с м. Кутузовская — гибридный формат работы — ежегодный пересмотр зарплаты, квартальная и годовая премия — корпоративный спортзал и зоны отдыха — более 400 образовательных программ СберУниверситета для профессионального и карьерного развития — программа адаптации и помощь руководителя на старте — расширенный ДМС, льготное страхование для семьи и корпоративная пенсионная программа — гибкий дисконт по ипотечному кредиту, равный 1/3 ключевой ставки ЦБ — подписка Прайм с возможностью совместного использования на трёх близких — вознаграждение за рекомендацию друзей в команду Сбера.