Staff Data Scientist - Product Analytics
Staff-level data scientist who will define product metrics, lead experimentation and causal analysis, mine complex datasets, and build data products for a B2B SaaS platform. The role requires 8+ years of quantitative experience, advanced SQL, Python or R, and ownership of dbt-based data pipelines.
About the job
Responsibilities
- Define, instrument, and analyze metrics for customer adoption, retention, engagement, feature adoption, activation, and value.
- Design and analyze A/B tests and quasi-experiments, applying causal inference when appropriate.
- Explore large product and contract datasets to identify patterns, opportunities, and strategic hypotheses.
- Partner with Product and Engineering to ship embedded analytics, benchmarks, insights, and AI-powered data products.
- Own and extend dbt models and transformations, including scalable, documented, tested data models and consistent warehouse and BI definitions.
- Structure data assets, documentation, and metadata for reliable use by humans and large language models.
- Provide technical direction, code and analysis reviews, and mentorship to analysts, data scientists, and analytics engineers.
- Communicate findings and recommendations to Product, Engineering, and senior leadership.
- Design and scale self-service analytics ecosystems, semantic layers, and data documentation.
Requirements
- 8+ years of experience in product analytics, data science, or a closely related quantitative field, with demonstrated senior- or staff-level impact.
- Deep expertise in product analytics, experimentation, A/B testing, funnel and retention analysis, causal inference, and product metrics.
- Advanced SQL and fluency in Python or R for analysis, statistics, and modeling.
- Experience owning dbt models, data modeling, and ELT best practices.
- Experience partnering with Product and Engineering to ship data products or data-informed features.
- Strong data-mining and exploratory analysis skills.
- Experience with, or strong interest in, AI-assisted development and AI-ready data.
- Familiarity with modern data stacks and equivalent tools.
- Ability to lead initiatives end to end, communicate clearly, and connect technical work to business impact.
Nice to Have
- Experience at a B2B SaaS company.
- Experience with Cursor or Claude Code.
- Familiarity with Segment, Fivetran, BigQuery, Airflow, Looker, or Hex.
Compensation and Benefits
- Base salary: $180,000–$220,000, plus company bonus.
- Equity awards, including a new-hire grant and opportunities for additional awards.
- Medical, dental, and vision coverage for employees, with dependent coverage options.
- Gender-neutral parental leave, compassionate leave, and paid time off.
- Family-forming support through Maven.
- Monthly wellbeing, hybrid-work, and applicable cell-phone stipends.
- Mental health support through Modern Health.
- Pre-tax commuter benefits.
- 401(k) plan with employer match.
- Regular team events and career-development opportunities.
Skills
SQL, Python, R, dbt, Data Modeling, ELT, A/B Testing, Causal Inference, Product Analytics, BigQuery, Airflow, Looker, Segment, Fivetran, Hex
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