Senior Product Data Scientist

Collective • San Francisco, CA

5d • $180,000 - $230,000 • 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 voice in product strategy, partnering with Product, Engineering, Operations, Finance, and Go-to-Market to turn member behavior across incorporation, bookkeeping, tax, and payroll into insights that shape the roadmap. The person in this role owns metrics and analysis behind key decisions end to end, from measurement definitions through data quality, and helps Collective grow and retain members while helping them save time and money.

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 a reliable foundation for the company. The role combines product analytics and data science with data engineering, including building trusted datasets and maintaining the documentation and semantic layer that support company decisions and internal data agents.

Requirements

• At least 6 years of experience in data science, product analytics, analytics engineering, or data engineering; experience at a B2B SaaS or fintech company is ideal.
• Bachelor's degree in mathematics, statistics, or a technical field, or equivalent practical experience.
• Ability to take initiative, investigate problems thoroughly, and bring ambiguous, high-impact questions through to a decision.
• Ability to work across product analytics and data engineering, including experiment analysis as well as pipeline or model troubleshooting.
• Expert SQL skills and strong Python or R scripting skills for analysis, statistics, and tooling.
• Hands-on experience transforming messy raw sources into trusted, tested datasets used by other teams, using a modern 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 inform launch decisions.
• Experience with Statsig, LaunchDarkly, or similar experimentation tools.
• Hands-on experience with Amplitude, Segment, Metabase, or similar product analytics tools.
• Ability to perform exploratory analysis with minimal direction and turn complex datasets into actionable insights.
• Strong product sense, including the ability to assess details of product experiences and generate growth ideas.
• Clear communication skills, including the ability to present compelling data narratives and explain trade-offs to product leads and cross-functional partners.

Nice To Haves

• Experience in a fast-paced, high-growth environment.
• Exposure to financial, accounting, tax, or payroll data and the high standards for correctness these domains require.
• 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, Engineering, Operations, Finance, and Go-to-Market stakeholders to share product insights, shape the roadmap, and challenge assumptions with evidence.
• Analyze large and messy datasets using first-principles thinking, and communicate clear findings and visuals that explain their implications for the product.
• Apply statistical and modeling techniques, including segmentation, cohort, retention, 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 for product strategy and key initiatives, maintaining one tested definition for each metric.
• Transform raw data from the product database, payments, support, and third-party tools through Fivetran and dbt in BigQuery into clean, tested, documented datasets.
• Address data problems at their source and add tests, monitoring, and lineage so data can be verified quickly.
• Maintain metric definitions, the semantic layer, and documentation so Claude and internal data agents can answer questions accurately.
• Take ownership of ambiguous, open-ended questions with minimal direction and deliver work with urgency, judgment, and attention to detail.

Benefits

• Hybrid work model with in-office and remote flexibility.
• Fresh lunch provided on in-office days.
• $150 monthly reimbursement for transit expenses.
• $200 quarterly wellness reimbursement.
• Flexible PTO 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 events and an annual in-person summit.

What This Job Offers

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