Leads technical strategy for product experience, building predictive models for matching optimization, growth flywheels, and marketplace health. Partners with PMs on experimentation, causal inference, and data platform design using SQL/Python expertise. Requires 8+ years in data science.
195k – 235k/yr
Remote8+ YOEData Science
About the role
Responsibilities
Act as a Strategic Thought Partner: Partner directly with Product Managers and other leaders to frame key business problems, define our measurement strategy, and guide product innovations.
Architect Marketplace Intelligence: Build and deploy sophisticated predictive models to refine Kindred’s matching algorithms, optimizing for growth, trust and liquidity.
Lead and Scale Experimentation: Own the end-to-end experimental framework, applying advanced causal inference to measure the ripple effects of product changes on community sentiment and marketplace health.
Own the Full-Stack Data Lifecycle: Lead the design of robust event structures with Product Engineers and collaborate with Data Engineering to build a scalable data platform that ensures our data is "born clean" and ready for modeling.
Influence and Educate: Translate complex analytical concepts into clear, actionable recommendations and effectively persuade senior stakeholders to adopt data-informed strategies.
Requirements
Experience: 8+ years of experience in a quantitative role such as data science, with a proven track record of influencing strategy at a leadership level, preferably within a consumer tech or marketplace company.
Full-Stack Practitioner: Expert in SQL and Python/R, with a proven ability to move a project from a whiteboard concept to a production-grade ML model, and experience with modern data warehouses.
Mastery of Causal Inference and Experimental Design: Deep experience going beyond simple A/B tests to measure product impact in networked environments where interference and spillover are present.
Leadership & Influence: Exceptional communication skills, with a proven ability to simplify complex concepts and persuade senior stakeholders to trust the data and embrace new measurement strategies.
Nice-to-Haves
Think in Systems, not just Features: Naturally consider "spillover effects"—understanding how a boost in one area of the platform might impact another part of the community ecosystem.
Technical Force Multiplier: Track record of leveling up the teams around you, setting the standard for code quality, and effectively communicating complex technical risks to non-technical partners.
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