Associate Analytics Team Leader — Intercity
Skills required
About this role
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.
Key Responsibilities
- 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
Skills, Knowledge and Expertise
- 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