Senior Product Insights Analyst

• 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
• Build, evaluate, and productionalize models to forecast outcomes such as patient retention, no shows, demand patterns, and more
• Balance technical sophistication with pragmatic application, recognizing when simpler analyses can achieve the same business impact
• 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
• 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
• Collaborate with Data Engineering and BI 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

• 4+ years of experience in product insights, 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
• Practical understanding of ML modeling trade-offs: when to deploy advanced models vs. when a well-structured analysis is the right tool
• Understands the spirit of George Box’s reminder that “all models are wrong, but some are useful” and applies that judgment to build solutions that balance sophistication with pragmatism
• 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, but not required
• Experience on a Product growth team, where experimentation and opportunity identification were key aspects of the role, is a plus

medical, dental, vision, effective day 1 of employment, 401K with match, generous PTO plus paid holidays, paid parental leave