Analyst for the Pay Card Efficiency Team in Fintech

The Pay debit card is one of Yandex's key fintech products. We are developing it as a universal tool for daily payments, earning rewards, and using services for millions of users. We launch and scale modern loyalty mechanics: cashback, referral programs, promotional campaigns, to make the card the center of financial life.

The Pay Card Efficiency analytics team ensures that every ruble of promotional investment contributes to product growth. We analyze internal and external promotion channels, build analytical pipelines from scratch, evaluate the effectiveness of tools, and provide recommendations on budget allocation.

Our team has deep access to data across the entire user journey within the Yandex ecosystem. This allows us to go beyond point promotions and, through systematic analysis, increase loyalty and develop long-term strategies for user retention, cross-selling, and increasing the product's value for them.

We are not just making a card — we are changing how people build their financial lives. We need those who love breaking down complex tasks into simple insights, can get excited by numbers, and are passionate about creating products they would want to use themselves. Join us — together we will make the Pay card indispensable!

What tasks await you

Optimization of promotional channels You will research the effectiveness of cashback, referral and promotional mechanics, find growth points in attracting and retaining customers, and look for ways to optimize the budget.

Building analytical pipelines and BI dashboards You will create automated reports for the product and top management, visualize key metrics on user growth, quality of new tools, and the impact of promotions.

A/B testing You will work closely with A/B tests: from designing and launching them to deep analysis of results, interpreting effects, and developing recommendations for improvement.

Research and modeling You will need to dive into researching non-standard hypotheses, build uplift models, predict user behavior, and search for the most effective combinations of loyalty mechanics.

Strategic recommendations Based on data analysis and user needs, you will propose new tools and promotional mechanics to ensure the scalable and systematic growth of the Pay card within the ecosystem.

More about analytics at Yandex — in the channel Yandex for Analytics

We expect that you

• Have analyzed data in Python (Pandas, NumPy, visualization)
• Have applied advanced analytics (forecasting, ML modeling, uplift modeling) or are willing to learn to work with it
• Are excellent at SQL and know how to work with large volumes of data
• Can design and automate pipelines, BI dashboards (Tableau, Looker, PowerBI, Superset)
• Deeply understand A/B testing (design, statistics, interpretation)
• Understand the product analytics cycle (from hypothesis and mechanics design to impact evaluation and recommendations)
• Think systematically and look for insights in large data sets
• Can work with unstructured tasks and make decisions under uncertainty
• Know how to communicate results to different stakeholders

Will be a plus

• Have worked in fintech, e-commerce, or with payment systems
• Have conducted A/B tests on payment products
• Know what constitutes the unit economics of a debit card or other fintech products
• Know how to work with ecosystem products (e.g., loyalty programs, BNPL)
• Are familiar with cohort analysis methods, LTV, retention
• Understand the structure of Yandex's infrastructure (YT, MapReduce, ClickHouse)
• Know how to automate routine tasks (from reports to data validation)
• Understand the logic of user behavior in mobile applications
• Understand how data influences product decision-making