Senior Product Data Scientist
Senior individual contributor Product Data Scientist driving growth analyses, experimentation, and applied analytics for a mental health tech platform. Owns opportunity sizing, experiment design, and cross-functional insights for Product, Engineering, and Operations stakeholders.
Proactive Insights & Storytelling
- Identify growth opportunities for the Product teams by analyzing data and understanding patient behaviors
- Help Product teams maximize impact by working with PMs and engineers to understand costs and constraints, while looking at underlying data and making reasonable assumptions to size opportunities
- Identify risks by exploring data and monitoring trends to understand the impact of emerging issues before they become problems
- Frame analyses and estimates in terms of “so what” for the practice to ensure findings don’t just inform, but influence the team
- Develop regular deliverables that turn historical data into forward looking guidance for product and operational teams
- Anticipate questions our teams should be asking and bring forward insights before they’re requested
Experimentation & Measurement
- Partner with Product and Operations teams to design experiments, define success metrics, and implement robust statistical evaluation frameworks
- Ensure appropriate statistical power, so results are both valid and actionable
- Analyze experiment results and establish clear post experiment communication, ensuring learnings (positive or negative) are codified and inform future product or operational decisions
Applied Analytics
- Lead analyses on patient growth, clinician utilization, marketplace dynamics and more to surface actionable insights to leadership
- Translate adhoc analyses into repeatable frameworks and scalable reporting so insights don’t stay one-off, but become institutional knowledge
Collaboration
- Collaborate with Data Engineering and Analytics Engineering teams to define requirements and highlight gaps, so that data pipelines reliably support advanced analytics and modeling
- Act as a thought partner to Operations, Clinical, and Finance leaders, not just answering questions, but shaping the questions we should be asking
Requirements
- 4+ years of experience in data science, analytics, or related fields, with a track record of delivering measurable business impact
- Advanced proficiency in Python (pandas, scikit-learn, statsmodels and all other common data science packages) and SQL
- Experience with modern data warehouses (Snowflake, Redshift, BigQuery)
- Strong foundation in experimental design, causal inference, and statistical methods
- Exceptional communication skills, displaying the ability to frame technical findings in a way that resonates with stakeholders
- Strong applied experience in data science is essential
- A Master’s or PhD in a quantitative field is a plus
- Experience in DBT is a plus
- Experience on a Product growth team, where experimentation and opportunity identification were key aspects of the role, is a plus
Benefits
- Excellent benefits: medical, dental, vision effective day 1 of employment
- 401K with match
- Generous PTO plus paid holidays
- Paid parental leave
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