Senior Product Data Scientist

About Collective: Collective is on a mission to redefine the way businesses-of-one work. Our technology and team of trusted advisors help members achieve financial independence by taking care of everything from business incorporation to accounting, bookkeeping, tax services, and access to a thriving community, all in one integrated platform. We believe in empowering self-employed people to enjoy the same tax savings that big companies get, so they can focus on their passion, not paperwork. Featured in Forbes, Business Insider, Yahoo, Bloomberg, Financial Times, TechCrunch, and more. We are backed by General Catalyst, Sound Ventures, QED Investors, Google’s Gradient Ventures, Expa, and other investors who have financed iconic companies like YouTube, Substack, Twitch, Box, Hims, Instacart, and Lyft. About the role: We’re hiring a Senior Product Data Scientist to build and evolve the core product experiences that power Collective’s member platform. You’ll be the analytical voice in product strategy, working with product, engineering, Operations, Finance, and Go-to-Market to turn member behavior across incorporation, bookkeeping, tax, and payroll into clear insights that shape the roadmap. You’ll own the metrics and analysis behind key decisions end to end, from defining what we measure to making sure the underlying data holds up. This role directly shapes how we help self-employed members save time and money, and how we grow and retain them. This is a hands-on role for someone who cares about data quality, takes ownership of production systems end-to-end, and wants their work to be the foundation the rest of the company builds on. What you'll do: - Drive product strategy with stakeholders. Work closely with product leads, engineering, Operations, Finance, and Go-to-Market. Share product insights regularly, shape the roadmap, and push back with evidence when the data says something different. - Lead product analytics. Approach problems from first principles and turn large, messy datasets into clear analysis and visuals that get to the "so what" and drive product insights across incorporation, bookkeeping, tax, and payroll. - Use data science to uncover member behavior. Apply statistical and modeling techniques such as segmentation, cohort, retention, and churn analysis to understand what members do, why they do it, and what it means for the product. - Find and size growth. Identify opportunities to grow membership and retention, size them, and help product leads prioritize what to build for the biggest long-term impact. - Own the metrics. Define, build, monitor, and report on the metrics behind product strategy and key initiatives, with one tested definition for each. - Build the data you analyze. Take raw sources (our product database, payments, support, and third-party tools) through Fivetran and dbt in BigQuery into clean, tested, documented datasets that the whole company can use. Fix problems at the source, not downstream. - Keep it trustworthy. Add tests, monitoring, and lineage so a number can be checked in minutes rather than believed on faith. - Make the data agent-ready. Maintain the definitions, semantic layer, and documentation that let Claude and our internal data agents answer questions correctly for anyone making a decision. - Work with urgency and judgment. Pick up ambiguous, open-ended questions with minimal direction, and deliver with attention to detail. What you'll bring: - Experience: 6+ years in data science, product analytics, analytics engineering, or data engineering, ideally at a B2B SaaS or fintech company. A bachelor's degree in mathematics, statistics, or a technical field, or equivalent practical experience. - An owner's mindset: you are curious, keep asking "why" until you reach the bottom of a problem, and take initiative without waiting for a ticket. You take ambiguous, high-impact questions and see them through to a decision. - Range across both sides: you may be stronger in one, but you can do real work in the other. You can run an experiment analysis on Monday and fix a broken pipeline or model on Tuesday. - SQL and Python (or R): expert SQL and strong scripting for analysis, statistics, and tooling. - Data engineering you have done yourself: you have taken messy raw sources to trusted, tested datasets that other teams rely on, using a modern stack such as BigQuery, dbt, and Fivetran or similar. You know what good data looks like. - Experimentation: you design and interpret A/B and multivariate tests, understand power and guardrails, and build frameworks that turn results into launch decisions. Experience with Statsig, LaunchDarkly, or similar. - Product analytics: hands-on with Amplitude, Segment, Metabase, or similar. You turn complex datasets into actionable insights, and you can run exploratory analysis with minimal direction. - Product sense: you think through the detailed elements of a product experience and bring creative ideas for growth. - Communication: you tell clear, compelling stories with data and explain trade-offs to product leads and cross-functional partners. Nice to have: - Experience in a fast-paced, high-growth environment - Exposure to financial, accounting, tax, or payroll data and the correctness bar that comes with it - Experience building semantic layers or metric stores that LLM-based tools query, or running LLM evaluations - AI-assisted development experience (Claude Code or similar) - Prior consulting or investment banking experience - Reforge or similar growth and product certifications What we offer: - Hybrid Work Model: Based in San Francisco with a balance of in-office and remote flexibility. - Fresh Lunch: Provided on in-office days. - Commuter Support: $150 monthly reimbursement for transit expenses. - Health & Wellness: $200 quarterly reimbursement to support your well-being. - Time Off: Flexible PTO plus 14 company holidays. - Comprehensive Coverage: 100% medical, dental, and vision for employees; 75% coverage for dependents. - Parental Leave: 16 weeks fully paid. - Retirement & Ownership: 401k plan plus an equity package. - Team Connection: Quarterly virtual events and an annual in-person summit.