Staff Economist, Marketplace Experimentation

About the role

This Staff Economist position at Bolt focuses on enhancing the company's two-sided marketplaces. The core work involves applying advanced econometric and statistical theories to optimize pricing, matching, and commissions. A key responsibility is to improve the sensitivity and speed of switchback tests, ensuring that measurement methods accurately capture value and address network effects.

The role involves significant research and development, aiming to deepen the understanding of marketplace dynamics. This includes implementing new methods to measure long-term impact and delivering proof-of-concepts that can be scaled company-wide by engineers. Collaboration with various marketplace teams is essential to provide guidance and develop solutions for specific challenges.

Success in this role means transforming how Bolt measures value across its platforms. This involves not only applying theoretical knowledge but also translating complex research into practical, scalable solutions. The economist will drive impactful business decisions by ensuring robust experimentation and a clear understanding of causal effects in a dynamic marketplace environment.

The listed salary range for this full-time Staff Economist position is $90,000 to $135,000 USD annually.

Skills that matter here

• econometrics: This role requires applying econometric theory to business decisions, specifically for optimizing marketplace operations.
• causal inference: The economist will use causal inference methods to inform product and policy decisions within the marketplace.
• Python: The ability to translate mathematical notation from research papers into working Python proof-of-concepts is necessary.
• data science: The role involves applying data science principles at scale, particularly with big data tools.
• Spark: Experience with big data tools like Spark is required for data science at scale.
• Databricks: Experience with big data tools like Databricks is required for data science at scale.

Who this role suits

• You have a strong academic background (PhD or equivalent) in economics or statistics.
• You thrive in collaborative environments, working with diverse teams to solve complex problems.
• You are self-directed and capable of defining your own roadmap, while also being open to support and context.
• You enjoy translating theoretical research into practical, scalable solutions for real-world business challenges.

From the employer

• Collaborate with marketplace teams across the company to optimize sensitivity and speed of their switchback tests
• Provide standardized guidance to teams on network effects and how to select the right measurement methods.
• Drive R&D to deepen our understanding of marketplace dynamics and implement new methods to measure long-term impact
• Deliver proof-of-concepts clear enough for engineers to platformise and scale company-wide

• A strong background (PhD or equivalent experience) in the application of econometric or statistical theory to business or policy decisions
• Work well in highly collaborative environments to understand the context-specific challenges of teams and work with them to find and develop solutions
• Proven experience in applying causal inference methods to real product or policy decisions, with at least a theoretical understanding of two-sided marketplaces
• Comfort reading and implementing methods from research papers: you can go from a paper's mathematical notation to a working Python proof-of-concept
• Self-direction to define your own roadmap and drive it – you will have strong support and context along the way
• Experience with data science at scale using big data tools like Spark/Databricks
• Experience is great, but we really look for drive, intelligence, and integrity.