Responsibilities
- Drive pricing intelligence: design and implement Machine Learning models and optimization algorithms that directly fuel a comprehensive suite of pricing levers
- Own projects end to end: from problem definition and metrics design, through data extraction and model implementation, to presenting results to business and product stakeholders.
- Collaborate with data scientists and backend engineers to translate models into production-ready features
- Design and analyze experiments to measure the impact of fee strategies or model changes.
- Leverage statistical analyses to uncover actionable insights and inform critical tech, business and product decisions
- Communicate your work clearly to engineering, product, and business stakeholders.
Requirements
- At least 5 years of industry experience as a data scientist
- Master’s (or PhD ) in a quantitative discipline such as Statistics, Economics or Engineering
- Impact-driven: You’ve contributed to data science projects that made a real impact on live, customer-facing products — not just in theory, but in production.
- Comfortable with ambiguity: you are able to make decisions and propose directions even when the problem is not fully defined or the data is imperfect
- Strong grasp of machine learning and statistical concepts and know how to choose the right model for the problem and make it work in a production environment.
- Practical expertise in experimentation design and analysis.
- Proficient in Python and SQL, and familiarity with software engineering principles around testing, code reviews, and deployment
- Clear communicator: You are comfortable explaining complex ideas and results to diverse audiences, including senior management.
Nice to Have
- Experience in pricing, B2C marketplaces or revenue management
Work Arrangement
Hybrid
Additional Information
- Hybrid work environment, with 2 remote days a week and 1 remote work week per quarter, plus 3 flex days.
