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.
