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.
145k – 180k/yr
Remote4+ YOEData Science
About the role
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
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