Clinical Data Scientist

Counsel Health•New York, NY

About The Position

At Counsel Health, we’ve spent the last few months building a world-class data foundation. Our infrastructure engineers have stood up our data warehouse; now, we need the "brain" to operate it. We are looking for a Clinical Data Scientist who bridges the gap between complex health data and actionable business intelligence. You won’t be building the warehouse from scratch (the 0-to-1 infra work is done), but you will be the primary architect of how we use that data. You will build the views, run the population health analytics, and ensure that we never have to manually dump data into an Excel sheet ever again!

Requirements

3+ years of experience in Data Science or Analytics, specifically within the Healthcare or HealthTech space.
Deep expertise in SQL (dbt experience is a plus).
Strong experience with data visualization/BI tools (Hex, Tableau, Sigma, etc.).
Proven ability to work with de-identified datasets and maintain high standards of data privacy/security. (Familiarity with HIPAA safe harbor de-id is a plus).

Nice To Haves

Experience joining diverse API-based data sources (Stripe, CRM, Clinical APIs).

Responsibilities

Own the Analytics Layer: You’ll be the expert on our data warehouse, building and maintaining the SQL views and transformations that power our internal reporting.
Clinical Population Health: Analyze de-identified health data to monitor anti-microbial stewardship, clinical outcomes, and patient trends. You’ll help us drive towards a holistic understanding of our users health concerns and outcomes.
Business & Growth Intelligence: Join disparate data sources (internal and external) to answer the "hard" questions that shape our business direction and strategy, working closely with our SVP of Finance & Operation.
Democratize Data: Implement and own our AI-first BI/visualization tooling (e.g., Hex, Sigma, or similar). Your goal is to make the rest of the team self-sufficient so they can answer their own data questions in real-time.
Bridge to Engineering: Work closely with the AI team creating reverse-ETL & intelligence layers so support projects like feeding clinical summaries back into our models and enabling near real-time clinical intelligence.
Operational Excellence: Turn "reporting" from a manual process into an automated, living dashboard.