Аналитик продаж

An Overview of this role

As a Data Scientist at GitLab on the Enterprise Analytics team,  you’ll be a trusted analytical partner to Sales, Revenue Operations, and Finance, helping define how we measure go-to-market performance and where we invest to grow. This is a strategic and hands-on role. You’ll apply statistical, experimentation, and machine learning methods to forecast outcomes, explain what drives activation, conversion, expansion, and retention, and size opportunities. You’ll also support the company-level reporting and GTM performance views that executives use to run the business, covering consumption, ARR, and first orders.

What you’ll do

• Embed yourself with business teams to become a trusted partner supporting insight generation and strategic decision making across GTM.
• Perform exploratory data analysis to uncover behavioral trends, long-term patterns, and the key drivers and levers behind business performance, and communicate their impact clearly to non-technical audiences.
• Build and productionize machine learning models - such as propensity, product-qualified lead (PQL) scoring, churn, and expansion models - including training, validation, testing, and feature engineering, using MLOps practices and tooling (CI/CD for ML pipelines, model registries, automated retraining, and monitoring) to move work reliably from notebook to production
• Design, run, and evaluate growth experiments (A/B tests and quasi-experiments) on onboarding, pricing and packaging, and upgrade flows, and measure their impact on activation, conversion, and retention
• Build and operationalize agentic workflows for analysis, modeling, and pipeline automation, with evaluation and monitoring that keep agent-generated insights accurate, traceable, and trustworthy.
• Contribute to GitLab’s Semantic Layer enabling stakeholders and agents to self-serve metrics using trusts and tested sources.
• Write production-grade Python and SQL that meets internal standards for style, maintainability, and performance in a high-scale database environment; maintain and advocate for these standards through code review

What you’ll bring

• 3-5 years of professional experience in GTM analytics, data science, or a similar technical role
• Demonstrated ability to translate ambiguous business problems into clear, measurable questions and communicate technical concepts effectively to non-technical stakeholders.
• Experience with experimentation and causal inference (A/B testing, power analysis, quasi-experimental methods) and with statistical and machine learning methods such as regression, classification, clustering, and survival analysis
• Deep, hands-on understanding of SQL in cloud data warehouses (like Snowflake SQL), including working with product usage and event data, and in business intelligence tools (Looker, Tableau, Hex, or similar)
• Experience using Python for statistical modeling, machine learning, and production data science. With hands-on experience in pandas, NumPy, scikit-learn, Jupyter, and related libraries such as LightGBM and XGBoost
• Hands-on experience building agentic workflows with AI coding agents (e.g., Claude Code, OpenCode, or similar), including connecting agents to the right context, tools, and platforms such as MLflow, and evaluating their output for accuracy and reliability.
• Experience working in a B2C company working with motions and metrics, including Consumption, CRR, ARR, and Churn & Contraction
• Self-motivated and self-managing, with strong organizational skills
• Ability to use GitLab and to thrive in a fully remote organization

About the Team

The Enterprise Analytics team builds the trusted data products and insights behind GitLab’s Company wide sales, revenue, and finance reporting. We work across the business on metrics including First Orders, pipeline, CRR, ARR, and other key indicators, helping leaders make informed decisions and teams understand how their work contributes to GitLab’s growth.

An Overview of this Role

As Senior Manager, Data Science, you'll lead Product Data Science: a team of 6 Data Scientists within GitLab's data organization, reporting to the Director of Data Science. You have two mandates:

1. Drive product impact now. Set the analytical agenda for your product areas and make sure the team's work changes decisions.
2. Build the merged Data Science function. Define excellence for a Data Scientist who blends analytics and data science, and grow the team to that bar.

You lead mainly through others, and step in hands-on when it matters: reviewing a model, pressure-testing an analysis, or writing the query yourself.

What you’ll do

• Set a long-range vision and roadmap for Product Data Science, and show the team how its goals connect to company strategy
• Own prioritization and trade-offs across product areas, and adapt the team as priorities shift
• Be the go-to partner for Product and Engineering leaders on complex and urgent questions, choosing the right approach: a deep dive, an experiment, or a production model
• Raise risks and resource gaps early, and bring senior leaders clear options to drive timely decisions
• Hire, coach, and retain a high-performing team: build career paths, act on team feedback, and make tough talent decisions when needed
• Build a high-trust culture of urgency and accountability, where the team communicates openly, shares progress on a predictable cadence, and delivers quality results on time
• Set standards for experimentation, causal inference, metric definition, and production modeling

What you’ll bring

• 10+ years in data science, product analytics, or a related field, including 3+ years managing data science or analytics teams in B2B SaaS or tech
• Strong product sense and a track record as a trusted partner to Product and Engineering leaders
• Exceptional communicator who makes complex problems and findings clear to any audience, from Product leaders to executives, and coaches others to do the same
• Thrives in ambiguity: structures undefined problems, gathers the right information, and makes sound decisions on high-risk, cross-team issues
• Courage to challenge: offers dissenting views, asks tough questions, and fosters inclusive debate
• Deep expertise in statistics and experimentation, including hands-on use of quasi-experimental methods (difference-in-differences, synthetic control, propensity score matching)
• Expert SQL (Snowflake preferred) and strong Python, with experience taking ML models to production
• Fluent with AI tools, with sound judgment on when AI output can be trusted
• Able to use GitLab, thrive in an all-remote, asynchronous company, model GitLab's remote working competencies, and work in line with GitLab's values

Nice to Have

• Experience with developer tools, DevSecOps, or product-led growth products
• Experience measuring adoption and quality of AI-powered product features
• Thought leadership in data science or analytics, internally and externally
• Advanced degree in a quantitative field

About the Team

Product Data Science brings Data Science and Analytics together into one function. Our Data Scientists are business partners first, pairing strong product judgment with deep skill in SQL, Python, statistics, and machine learning. We help Product and Engineering decide what to build, measure what worked, and understand how customers get value from GitLab.

The opportunity is growing fast. AI is driving growth in GitLab's consumption business, creating new ways for data to drive growth. As AI takes over routine reporting, the team focuses on the hard problems: experimentation, causal inference, production models, and recommendations leaders act on.

Компания ООО ИЦ «АЙ-ТЕКО» - ведущий российский системный интегратор и поставщик информационных технологий для корпоративных заказчиков. Активно действует на рынке IT России с 1997 года, входит в ТОП-400 крупнейших российских компаний, ТОП-10 крупнейших IT-компаний России.

В связи с активным развитием проектов в компании открыта вакансия Аналитик данных.

НАШИ ОЖИДАНИЯ ОТ УСПЕШНОГО КАНДИДАТА:

• Уверенное знание SQL (вложенные запросы, оконные функции, CTE);
• Понимание логики реляционных СУБД;
• Опыт исследований больших данных;
• Опыт работы с Hadoop;
• Опыт работы с Greenplum;
• Базовое понимание Airflow;
• Умение проверять качество и полноту данных;
• Умение переводить бизнес-задачу в измеримые показатели и алгоритмы;
• Навыки документирования аналитической и бизнес-логики;
• Желание разбираться в бизнес-контексте;
  

БУДЕТ ПЛЮСОМ:

• Понимание ML-скорингов (propensity/response/uplift моделей);
• Опыт AB-тестирования;
• Опыт работы с клиентскими коммуникациями, CRM или campaign management;
• Понимание задач оптимизации и ранжирования;
• Опыт работы с B2B-данными;
• Знание банковских продуктов корпоративного бизнеса.

МЫ ПРЕДЛАГАЕМ:

• Работа в аккредитованной ИТ-компании;
• Оформление в соответствии с ТК РФ с первого дня работы;
• Формат работы: Фулл-тайм офис в Москве по адресу - Кутузовский пр. 32;
• ДМС с первого дня работы (включая стоматологию);
• Корпоративный спорт: скидки на посещение фитнес-клубов, футбольная и волейбольная секции, собственный йога класс;
• Работа в команде, использующей гибкий подход к разработке;
• Работа в развивающемся IT-проекте с командой специалистов высокого уровня, возможность развития и обмена опытом.