NexHealth's mission is to accelerate innovation in healthcare. The healthcare industry is stuck in the 1990s while affordability and accessibility are spiraling out of control. NexHealth’s goal is to create an open and modern ecosystem to accelerate innovation in the space. The Staff Data Scientist will design NexHealth’s financial data foundation from the ground up: the pipelines, models, and dashboards that power revenue reporting, forecasting, and decision-making across the company.
Requirements
- building or maintaining financial data systems using Snowflake, dbt, and a BI tool such as Sigma, Looker, or Tableau.
- modeling SaaS metrics (ARR, churn, CAC payback, retention, LTV) using SQL and a programming language such as Python or R.
- designing and automating data pipelines using APIs from Stripe, Chargebee, Salesforce, or similar platforms.
- implementing data quality testing, CI/CD, and version control practices for analytics.
- Strong skills with modern data stacks such as Snowflake, DBT, and Sigma (or similar BI tools)
- Deep understanding of SaaS financial metrics such as ARR, churn, retention, lifetime value, and CAC payback, and how to model them in SQL and code
- Experience designing automated data pipelines and forecasting systems using APIs from tools like Chargebee, Stripe, or Salesforce
Responsibilities
- design NexHealth’s financial data foundation from the ground up: the pipelines, models, and dashboards that power revenue reporting, forecasting, and decision-making across the company.
- move fast, ship scalable systems, and apply first-principles thinking to every modeling decision.
- building or maintaining financial data systems using Snowflake, dbt, and a BI tool such as Sigma, Looker, or Tableau.
- modeling SaaS metrics (ARR, churn, CAC payback, retention, LTV) using SQL and a programming language such as Python or R.
- designing and automating data pipelines using APIs from Stripe, Chargebee, Salesforce, or similar platforms.
- implementing data quality testing, CI/CD, and version control practices for analytics.
- translate quantitative insights into actionable recommendations for executive or product leadership.
Other
- A builder mindset: excited by blank slates, scaling impact through automation, and simplifying complexity through systems.
- Strong communication and storytelling skills that connect insights to decisions
- Strong ownership: Knows what needs to be done, and gets it done with little or no oversight.
- Bias for action: Outcome oriented. Delivers results fast.
- Acts with first principles: Describes the ideal end state with first principles, and helps us get there fast.
