Note: The job is a remote job and is open to candidates in USA. Gratia Health is a venture-backed healthcare technology startup that helps healthcare employers create healthier, more sustainable workforces through a behavior change platform. The Product Analytics Engineer will own the company’s data landscape by building behavioral models and personalization algorithms, maintaining dbt/Snowflake analytics workflows, and translating insights into product features, targeting, and content recommendations.
Responsibilities
- Build, evaluate, and refine predictive models—expanding our current relevance scoring model into automated content targeting and user personalization
- Apply statistical analysis and machine learning techniques to product event telemetry (PostHog) to understand user engagement patterns across core app mechanics like Compliment Circle, Care IQ, and Shift Pickup
- Maintain dbt transformation models in Snowflake and oversee the automated sync of model outputs (e.g., relevance scores) back into our production Postgres database via Airbyte
- Partner with engineering to establish clean PostHog tracking schema that serves as training data for ML models and feature analytics
- Proactively identifies opportunities to turn user interaction data into predictive features and personalized product experiences
- Balances statistical rigor with product execution—building simple, interpretable models first before jumping into heavy neural architectures
- Comfortably takes a model from PostHog event logging to dbt transformations, Python feature engineering, and production Postgres syncs
- Looks at the data and makes it say something
- Partners with product, engineering, and leadership teams to understand data needs
- Designs and implements data schemas and collection patterns that integrate seamlessly with our application
- Collaborates with engineering team to ensure the application captures the right data in the right format
- Advocates for data-driven decision making across the organization
- Excellent remote communication skills, working effectively with a distributed team
Skills
- 2+ Years Experience: Background as an Analytics Engineer, Product Analyst, or Product Data Engineer
- Modeling & ML Proficiency: Hands-on experience building user-level or predictive models using Python (pandas, scikit-learn, and exposure to PyTorch or TensorFlow)
- Statistical Rigor: Strong foundation in statistics, user segmentation, hypothesis testing, and behavioral data modeling
- Data Engineering Competency: Advanced SQL fluency, experience writing dbt models in Snowflake, and familiarity with sync-back workflows to production databases
- Product-Driven Execution: Ability to connect mathematical models directly to product outcomes like engagement, retention, and content relevance
- Autonomy & Ownership: Comfortable serving as the single data owner on an engineering team, taking initiative without needing dedicated data management
- Targeting & Personalization Vision: Proactively identifies opportunities to turn user interaction data into predictive features and personalized product experiences
- Pragmatic Modeling: Balances statistical rigor with product execution—building simple, interpretable models first before jumping into heavy neural architectures
- End-to-End Ownership: Comfortably takes a model from PostHog event logging to dbt transformations, Python feature engineering, and production Postgres syncs
- Looks at the data and makes it say something
- Partners with product, engineering, and leadership teams to understand data needs
- Designs and implements data schemas and collection patterns that integrate seamlessly with our application
- Collaborates with engineering team to ensure the application captures the right data in the right format
- Advocates for data-driven decision making across the organization
- Excellent remote communication skills, working effectively with a distributed team
Benefits
- Remote work arrangement
- High levels of autonomy to produce the best work in the way that works best for them and the team
- An environment of kindness and generosity
- Collaborative remote team environment
Company Overview