Associate Analytics Team Leader — Intercity

You will lead analytics for our Intercity vertical — a core business driving long-distance travel across cities. This includes car-based rides as well as partner transportation networks such as buses and other regional operators. Your mission is to uncover opportunities for growth, optimize pricing and demand-supply balance, and help shape the future of intercity mobility for millions of users. You will manage a team that partners closely with product, operations, and marketing to improve unit economics, drive market expansion, and deliver a seamless experience for both passengers and drivers. From building forecasting models and demand-planning tools to analyzing new market entry strategies and measuring the impact of promotional initiatives, your work will directly influence business-critical decisions. In this role, you will act as a trusted advisor to product and business stakeholders — aligning analytics with strategic priorities, driving data-informed decisions, and creating scalable processes for the fast-growing Intercity vertical.

Lead, mentor, and develop the analytics team, supporting performance, growth, and professional development
Define and drive the analytics strategy, roadmap, and standards aligned with business and product objectives
Oversee key metrics, experimentation, and analytical outputs to ensure quality, consistency, and impact
Partner with product, engineering, and business leaders to embed data-driven decision-making across the organization
Establish and continuously improve analytics processes, documentation, and governance
Ensure data quality, integrity, and effective cross-team data collaboration

5+ years of experience in data analytics or data science
2+ years of people management, leadings of 5+ people
Analytical mindset: structured and critical thinking, the ability to find a balance between the resources spent and the effect on the business
Strong mathematical background with an emphasis on mathematical statistics, optimization theory, time series and causal inference
Proficiency in Python and data analysis libraries
Proficiency in SQL: ability to work with large amounts of data, write and optimize complex queries, create analytical data marts
Experience in creating BI reports: Plotly / Redash / Tableau
English: Professional Working Proficiency