Head of Product Data Science

About Abridge

Abridge was founded in 2018 with the mission of powering deeper understanding in healthcare. Our AI-powered platform was purpose‑built for medical conversations, improving clinical documentation efficiencies while enabling clinicians to focus on what matters most—their patients.

Our enterprise‑grade technology transforms patient‑clinician conversations into structured clinical notes in real‑time, with deep EMR integrations. Powered by Linked Evidence and our purpose‑built, auditable AI, we are the only company that maps AI‑generated summaries to ground truth, helping providers quickly trust and verify the output. As pioneers in generative AI for healthcare, we are setting the industry standards for the responsible deployment of AI across health systems.

We are a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. We have offices located in the Mission District in San Francisco, the SoHo neighborhood of New York, and East Liberty in Pittsburgh.

As the Data Science Leader at Abridge you will be responsible for building a world‑class data team, implementing a comprehensive data strategy that can help democratize data in the age of AI, and use data to drive actionable insights. We’re looking for a leader who has high‑agency, strong taste, and wants to make a high impact while growing our U.S. based team.

This role is crucial to our company as the Data Science team will serve as a central resource to provide insight and clarity while speeding up decision making. Your key cross‑functional partners will include our Product, Engineering and Science teams, as well as our commercial and finance teams to ultimately help guide our decision making.

As the leader of our data science function, you’ll be responsible for:

• Build and manage a world‑class team of data scientists, providing guidance, mentorship and high standards while growing the team to 12+ over the next twelve months

• Foster a high impact and collaborative team culture, focused on having agency, providing clarity of thinking to the organization and pride in authorship

• Drive product strategy through data‑driven insights across our growing product portfolio, including user behavior analysis, deep‑dives into product performance metrics, casual inference experimentation

• Partner with our product, strategy and research teams to develop sophisticated ROI frameworks for our customers, ingesting real‑time data and demonstrating impact

• Collaborate with our world‑class research team on models and model evaluation, including shaping our model evaluation frameworks, production performance monitoring, and defining quality metrics that matter clinically

• Effectively communicate our data strategy, complex analyses and key insights to cross‑functional partners including the executive team

• Structure the company’s data strategy, working closely with our Data Engineering team to identify gaps in data sources, ingest internal & external data, and structure that data for optimal use across the Company

• Make critical technical infrastructure decisions for the data organization, including tooling choices, build vs buy tradeoffs for analytics platforms, and setting technical standards that enable the team to move fast without creating technical debt

• Build the data science org of the future, incorporating the current and soon‑to‑come best practices in order to utilize AI to speed up data ingestion and insight generation

• MS or PhD in quantitative field (statistics, mathematics, computer science, physics, or related)

• 12+ years in data‑science or analytics, especially in product‑facing roles where you had to drive impact by using data to shape product strategy, goal setting and execution

• Depth of experience using Python, R, SQL for large‑scale analytics

• Comfort building data capabilities from the earliest stages through rapid growth, including interfacing closely with data engineering and machine learning

• Experience with data visualization tools, both BI tools (e.g. Tableau, Looker, Sigma) and code‑based tools (e.g. Seaborn, ggplot2)

• E…