Staff Data Scientist, Marketplace

Our Mission Healthcare should work for patients, but it doesn’t. In their time of need, they call down outdated insurance directories. Then wait on hold. Then wait weeks for the privilege of a visit. Then wait in a room solely designed for waiting. Then wait for a surprise bill. In any other consumer industry, the companies delivering such a poor customer experience would not survive. But in healthcare, patients lack market power. Which means they are expected to accept the unacceptable.   Zocdoc’s mission is to give power to the patient. To do that, we’ve built the leading healthcare marketplace that makes it easy to find and book in-person or virtual care in all 50 states, across +200 specialties and +12k insurance plans. By giving patients the ability to see and choose, we give them power. In doing so, we can make healthcare work like every other consumer sector, where businesses compete for customers, not the other way around. In time, this will drive quality up and prices down.    We’re 18 years old and the leader in our space, but we are still just getting started. If you like solving important, complex problems alongside deeply thoughtful, driven, and collaborative teammates, read on.   Your Impact on our Mission Zocdoc’s most important asset is our people. As a Staff Data Scientist, Marketplace, you’ll play a meaningful role in transforming healthcare by shaping how millions of patients discover and book care. The Marketplace team is responsible for driving patient demand, optimizing the search and booking experience, and ensuring a healthy, high-performing two-sided marketplace. This includes areas such as Growth, Search, Insurance, and Patient Home. As a strategic technical leader on the Marketplace Analytics team, you’ll design and scale analytical frameworks that inform product and growth strategy, guide experimentation, and optimize performance across the patient funnel—from acquisition through booking and retention. Your work will directly improve marketplace liquidity, efficiency, and long-term value. You’ll enjoy this role if you are… Passionate about transforming healthcare through data and turning complex datasets into meaningful product insights A force multiplier who loves mentoring and enabling teams to deliver scalable, high-impact work Comfortable operating at the intersection of business strategy, data science, and product innovation Energized by complex, ambiguous problems and skilled at translating them into structured analytical solutions Personally motivated by building systems, frameworks, and capabilities that outlast any one analysis Serious about your work, but not about yourself — you value rigor and humility equally Your day to day is… Partnering with Product, Marketing, Finance, Engineering, and Commercial teams to translate insights into actionable product and business strategy Architecting and executing experimentation frameworks, including A/B testing design, power analysis, variance reduction, and advanced causal inference methodologies (e.g., DiD, synthetic controls, propensity modeling, causal forests) Identifying, designing, and guiding the development of analytical models (e.g., LTV, survival, uplift models) to improve provider utilization, acquisition, retention, patient engagement, and client ROI Establishing scalable statistical frameworks and best practices to quantify the impact of product and commercial initiatives Partnering with Engineering to ensure data quality, event instrumentation, feature availability, and scalable pipelines that enable trustworthy analysis Mentoring and upskilling analysts and data scientists, raising the bar for analytical rigor and impact across Zocdoc Advancing AI-assisted analytical workflows to streamline recurring analysis and decision support Working with cutting edge GenAI tools and technology You’ll be successful in this role if you have… An unrelenting desire to build more equitable, inclusive, and diverse workplaces, and view this role as an opportunity to create positive change 8+ years of experience in data science, machine learning, or related quantitative roles Proven success developing LTV models, survival models, uplift models, or similar predictive frameworks for customer targeting and optimization Deep expertise in SQL and Python (pandas, NumPy, scikit-learn, statsmodels) Strong knowledge of experimentation and causal inference, including statistical power analysis, experiment design, and quasi-experimental methodologies Experience shaping and scaling analytics functions—not just building individual models Experience working in cross-functional product organizations The ability to integrate generative AI tools into daily workflows to automate tasks, foster innovation, and maximize productivity Superb communication skills and the ability to influence non-technical stakeholders