Senior Product Data Scientist

Collective • San Francisco, CA

3d • Hybrid

About The Position

Collective is hiring a Senior Product Data Scientist to build and evolve the core product experiences that power its member platform. The role serves as an analytical partner to product strategy, working with product, engineering, Operations, Finance, and Go-to-Market to translate member behavior across incorporation, bookkeeping, tax, and payroll into insights that shape the roadmap. The scientist owns metrics and analysis for key decisions end to end, including defining what to measure and ensuring the underlying data is reliable.

This is a hands-on role for someone who values data quality and takes ownership of production systems. The work directly informs how Collective helps self-employed members save time and money and how the company grows and retains its members. Responsibilities span product analytics and data science as well as data engineering: transforming raw sources through Fivetran and dbt in BigQuery into clean, tested, documented datasets; keeping metrics trustworthy through tests, monitoring, and lineage; and maintaining definitions, a semantic layer, and documentation for Claude and internal data agents.

Requirements

• At least 6 years of experience in data science, product analytics, analytics engineering, or data engineering; B2B SaaS or fintech experience is ideal.
• Bachelor's degree in mathematics, statistics, or a technical field, or equivalent practical experience.
• Expert SQL skills and strong Python or R scripting skills for analysis, statistics, and tooling.
• Hands-on experience taking messy raw data sources to trusted, tested datasets used by other teams, using a modern data stack such as BigQuery, dbt, and Fivetran or similar.
• Ability to design and interpret A/B and multivariate tests, understand statistical power and guardrails, and build frameworks that translate results into launch decisions.
• Experience with Statsig, LaunchDarkly, or similar experimentation tools.
• Hands-on experience with product analytics tools such as Amplitude, Segment, Metabase, or similar.
• Ability to turn complex datasets into actionable insights and conduct exploratory analysis with minimal direction.
• Product sense, including the ability to think through detailed product experiences and generate growth ideas.
• Clear communication skills, including the ability to tell compelling stories with data and explain trade-offs to product leads and cross-functional partners.
• Curiosity, initiative, and ownership: ability to pursue ambiguous, high-impact questions through to a decision and work across both analytical and data engineering tasks.

Nice To Haves

• Experience in a fast-paced, high-growth environment.
• Exposure to financial, accounting, tax, or payroll data and the associated correctness requirements.
• Experience building semantic layers or metric stores queried by LLM-based tools, or running LLM evaluations.
• AI-assisted development experience with Claude Code or similar.
• Prior consulting or investment banking experience.
• Reforge or similar growth and product certifications.

Responsibilities

• Partner with product leads, engineering, Operations, Finance, and Go-to-Market to share product insights, shape the roadmap, and use evidence to challenge assumptions.
• Analyze large and messy datasets using first-principles thinking, and present clear analysis and visuals that produce actionable insights across incorporation, bookkeeping, tax, and payroll.
• Apply statistical and modeling techniques, including segmentation, cohort analysis, retention analysis, and churn analysis, to understand member behavior.
• Identify and size opportunities to grow membership and retention, and help product leads prioritize work for long-term impact.
• Define, build, monitor, and report on metrics behind product strategy and initiatives, using a tested definition for each metric.
• Transform raw data sources—including the product database, payments, support, and third-party tools—through Fivetran and dbt in BigQuery into clean, tested, documented datasets.
• Fix data problems at their source rather than relying on downstream workarounds.
• Implement tests, monitoring, and lineage so data can be checked and trusted.
• Maintain metric definitions, a semantic layer, and documentation that enable Claude and internal data agents to answer questions accurately.
• Take on ambiguous, open-ended questions with minimal direction and deliver work with urgency, judgment, and attention to detail.

Benefits

• Hybrid work model based in San Francisco, with a balance of in-office and remote flexibility.
• Fresh lunch provided on in-office days.
• $150 monthly reimbursement for transit expenses.
• $200 quarterly reimbursement to support well-being.
• Flexible paid time off and 14 company holidays.
• 100% medical, dental, and vision coverage for employees; 75% coverage for dependents.
• 16 weeks of fully paid parental leave.
• 401(k) plan and an equity package.
• Quarterly virtual team events and an annual in-person summit.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior