Description:
As Data Science Manager, Product Analytics, you’ll be instrumental in uncovering insights that shape product strategy and performance. You’ll own A/B testing frameworks, lead data-driven experimentation, and deliver actionable recommendations that improve user engagement and retention. This role is a unique opportunity to combine cutting-edge analytics with a mission-driven focus on improving healthcare solutions.
Key Responsibilities
Product Analytics & Experimentation:
- Develop insights to enhance product engagement, optimize retention, and improve overall user experience.
- Design and implement A/B testing frameworks to measure the impact of product changes and personalization strategies.
- Leverage experimentation to refine user segmentation, inform feature development, and drive continuous improvement.
- Analyze patient data to uncover key trends that improve outcomes and inform product recommendations.
Driving Innovation in Product Analytics:
- Build churn prediction models and identify lapsed users to support marketing automation and re-engagement efforts.
- Develop leading indicators for retention and active user metrics to enhance decision-making.
- Partner with marketing and product teams to create data pipelines enabling robust user ID tracking and personalization.
- Collaborate on developing recommendation engines to enhance the user experience, with a focus on 2025 deployment.
Team Leadership & Execution:
- Oversee and manage two data scientists to execute the product analytics roadmap.
- Mentor junior team members, fostering a culture of analytical rigor and experimentation.
- Provide strategic guidance to leadership on applying analytics and testing to inform product-focused decision-making.
What We’re Looking For
Experience:
- 5+ years in data science, with a strong focus on product analytics and experimentation.
- Expertise in consumer or health tech, including DAU/MAU metrics, A/B testing, personalization, recommendation engines, churn prediction, and retention strategies.
- Experience with healthcare data (e.g., EPIC) is a strong plus.
Technical Skills:
- Required: Python, SQL.
- Preferred: Databricks, Azure Databricks.
Soft Skills:
- Exceptional ability to communicate data-driven insights and experimentation results to technical and non-technical stakeholders.
- Proven ability to lead roadmaps, deliver impactful analytics solutions, and foster a culture of testing and learning.
- A mentorship mindset, with experience developing junior staff and collaborating across teams.