Position not open anymore
Key Responsibilities
- Design and evolve the experimentation framework used across inDrive’s products (ride hailing, delivery, fintech etc.)
- Build and validate statistical methodologies for:
- A/B and multivariate testing
- Switchback testing
- Regional causal inference approaches
- Solve complex causal inference problems:
- Network effects, interference, non-compliance
- Long-term and delayed effects
- Heterogeneous treatment effects across markets
- Partner closely with engineers to translate statistical logic into scalable, production-ready systems
- Enable product teams by creating clear decision frameworks, metrics standards, and experiment review processes
- Drive adoption of advanced tools (e.g. CUPED, variance reduction, causal models)
Skills, Knowledge and Expertise
- 5+ years of experience in analytics, data science, or experimentation-heavy roles
- Strong foundation in statistics, probability, and causal inference
- Hands-on experience with A/B testing at scale
- Advanced SQL and Python (experience with experimentation or causal libraries is a plus)
- Ability to explain complex statistical ideas to non-technical stakeholders
- Product mindset: you care about decisions, not just numbers
- Curiosity, rigor, and the courage to challenge “obvious” conclusions
Conditions
- Stable salary, official employment
- Health insurance
- Hybrid work mode and flexible schedule
- Relocation package offered for candidates from other regions
- Access to professional counseling services, including psychological, financial, and legal support
- Discount club membership
- Diverse internal training programs
- Partially or fully paid additional training courses
- All necessary work equipment