Leading experimentation and analytical strategy across product, growth, monetization, marketing, and operational initiatives, often simultaneously
Applying causal inference methodologies (difference-in-differences, synthetic controls, propensity methods, Bayesian experimentation) to real business questions where traditional A/B testing may not be feasible
Partnering directly with directors and senior leaders to frame complex, cross-functional challenges and translate findings into clear recommendations that drive action
Improving experimentation frameworks, metrics strategy, and analytical rigor across teams — developing scalable approaches for measurement, segmentation, forecasting, and incrementality
Influencing roadmap prioritization and business strategy through rigorous analysis and precise communication of tradeoffs and uncertainty
Mentoring and upskilling data scientists and analysts across the organization on experimentation, causal inference, and statistical best practices
Partnering with Engineering, Product, and ML teams on instrumentation, data infrastructure, and analytics tooling
Integrating generative AI tools into daily workflows to automate tasks, foster innovation, and maximize analytical productivity

8+ years of experience in Data Science, Product Analytics, Applied Analytics, or Experimentation
Bachelor's degree in Computer Science, Data Science, Statistics, Applied Mathematics, Machine Learning, Artificial Intelligence, Economics, Physics, or a related field
Experience partnering with senior stakeholders across Product, Marketing, Revenue, Sales, Operations, or Customer Experience organizations to drive strategy through data
Strong experimentation experience at scale, including causal inference methodologies applied to real-world, often messy business settings
Advanced SQL proficiency and strong Python fluency, with the ability to work across large, complex datasets
The ability to integrate generative AI tools into daily workflows to automate tasks, foster innovation, and maximize productivity
Familiarity with areas such as: pricing and monetization analytics, growth and retention strategy, customer segmentation and lifecycle, marketing attribution and incrementality, or operational and marketplace analytics
Experience in fast-paced, high-growth environments — consumer technology, SaaS, fintech, marketplace, or platform companies is highly relevant
Humility — you believe in treating all people with dignity and respect, regardless of title or tenure.

Unlimited Vacation
100% paid employee health benefit options (including medical, dental, and vision)
Commuter Benefits
401(k) with employer funded match
Corporate wellness program with Wellhub
Sabbatical leave (for employees with 5+ years of service)
Competitive paid parental leave and fertility/family planning reimbursement
Cell phone reimbursement
Catered lunch everyday along with beverages and snacks
Employee Resource Groups and ZocClubs to promote shared community and belonging
Great Place to Work Certified

Staff Data Scientist, Marketplace Analytics

Key skills