Staff Product Data Scientist

Staff Data Scientist (Product)

Location: Remote

Salary: $190-220k

I'm partnering with a fast-growing SaaS company to find a Staff Data Scientist for a senior, high-visibility role embedded in their product organisation. This is for someone who combines deep statistical expertise with the ability to influence how an entire company makes decisions — not just someone who runs experiments, but someone who builds the culture and infrastructure around them.

What You'll Be Doing

• Owning and advancing the company's experimentation roadmap, focused on high-leverage product questions around customer workflows, churn risk, and long-term value
• Designing and analysing complex A/B tests, multivariate experiments, and Bayesian methods to measure the real impact of product changes
• Applying causal inference techniques (DiD, synthetic control, propensity score matching, instrumental variables) where traditional RCTs aren't feasible
• Building and governing a unified KPI framework that connects product health metrics to meaningful business outcomes
• Partnering with Data Engineering to build scalable, self-serve experimentation tooling and reusable analytical frameworks
• Translating complex statistical findings into clear, compelling narratives for VP and C-suite audiences
• Mentoring and training junior and mid-level data scientists on experimental design and causal modelling

What We're Looking For

This is a senior individual contributor role reporting to the Director of Product Data, acting as a strategic thought partner across Product, Engineering, Finance, Design, and Product Marketing. The company is at an inflection point in how it uses data to make product decisions, and this person will be central to shaping that.

Essential:

• 6+ years in applied data science, economics, or product analytics
• Proven expertise in causal inference: DiD, PSM, instrumental variables, quasi-experimentation
• Deep experience in A/B testing methodology including sequential testing, CUPED, variance reduction, and network effects
• Advanced SQL and Python or R for statistical modelling
• Experience with Snowflake or similar cloud data warehouses
• Exceptional communication skills, comfortable presenting to and influencing C-suite stakeholders
• Demonstrated ability to drive change in organisations where experimentation culture is still developing

Nice to have:

• Experience with dbt, Airflow, or Databricks
• Background in SaaS and product data science