This is a fully remote position, open to applicants in United States.

• Spearhead experimentation, business intelligence, and advanced analytics within our global two-sided marketplace.

• Take ownership of the company's experimentation strategy and enterprise BI operations.

• Collaborate closely with data engineering to develop reliable and scalable end-to-end data pipelines.

• Define and enhance the experimentation strategy.

• Ensure rigorous A/B testing and measurement of incrementality.

• Manage executive dashboards and enterprise reporting.

• Create and sustain a trusted metrics layer with established governance and definitions.

• Lead applied data science efforts in areas such as personalization, marketplace dynamics, pricing, segmentation, and lifecycle modeling.

• Collaborate with ML teams to ensure effective model evaluation and assessment of business impact.

• Act as a strategic advisor to executive leadership on data-driven growth strategies.

• Over 15 years of experience in Data Science, Analytics, or quantitative leadership positions.

• Proven track record of leading BI and analytics functions in a large, global organization.

• Successful experience operating within a two-sided marketplace or platform business.

• Demonstrated ability to own experimentation strategy and achieve measurable business outcomes.

• Experience collaborating with C-suite and Board stakeholders.

• Extensive knowledge of experimental design, causal inference, and statistical modeling.

• Proven experience in building scalable experimentation and analytics ecosystems.

• Proficient in SQL and contemporary data tools (e.g., Snowflake, Looker, Sigma, Tableau).

• Strong understanding of marketplace unit economics and lifetime value (LTV) modeling.

• Experience in developing and scaling high-performing Data Science and Analytics teams.

• Excellent cross-functional collaboration skills in matrixed environments.

• Capability to translate complex quantitative analyses into clear business insights.

• Medical

• Dental

• Retirement

• Generous leave policies

VP – Data Science

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