Head of Data Science

At Abridge, we’re transforming healthcare delivery experiences with generative AI, enabling clinicians and patients to connect in deeper, more meaningful ways. Our mission is to power deeper understanding in healthcare. We’re a growing team of practicing MDs, AI scientists, PhDs, creatives, technologists, and engineers working together to empower people and make care make more sense. Our offices are located in San Francisco, New York, and Pittsburgh.

About the role

As the Director of Data Science at Abridge, you will build and lead a world-class data team, implement a comprehensive data strategy, and use data to drive actionable insights. 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. You will partner with Product, Engineering, Science, commercial, and finance teams to guide our decision-making.

Responsibilities

• Build and manage a world-class team of data scientists, providing guidance, mentorship, and high standards while growing the team
• Foster a high-impact and collaborative team culture focused on agency, clarity of thinking, and pride in authorship
• Drive product strategy through data-driven insights, including user behavior analysis, product performance metrics, and causal inference experimentation
• Partner with product, strategy, and research teams to develop sophisticated ROI frameworks for customers using real-time data
• Collaborate with the research team on models and model evaluation, shaping evaluation frameworks, monitoring production performance, and defining clinically relevant quality metrics
• Effectively communicate data strategy, complex analyses, and key insights to cross-functional partners, including the executive team
• Structure the company’s data strategy, working closely with Data Engineering to identify gaps, ingest internal and external data, and optimize data use across the company
• Make critical technical infrastructure decisions, including tooling choices, build vs. buy tradeoffs, and setting technical standards to enable fast, low-debt growth
• Build the data science org of the future, incorporating best practices to utilize AI for faster data ingestion and insight generation

Requirements

• MS or PhD in a quantitative field (statistics, mathematics, computer science, physics, or related)
• 12+ years in data science or analytics, especially in product-facing roles where you used data to shape product strategy, goal setting, and execution
• Depth of experience using Python, R, and SQL for large-scale analytics
• Comfort building data capabilities from early stages through rapid growth, including close collaboration with data engineering and machine learning teams
• Experience with data visualization tools, including BI tools (e.g., Tableau, Looker, Sigma) and code-based tools (e.g., Seaborn, ggplot2)
• Excellent communication skills to deliver quantitative findings clearly and compellingly to non-technical stakeholders
• Strong leadership to build great teams, drive urgency, and prioritize effectively in a high-growth environment

Skills

• Bonus: Knowledge of healthcare settings, electronic health records (EHR), and healthcare billing
• Bonus: Experience shaping Analytics Engineering (recruiting and supporting)

Benefits

• Generous Time Off: 14 paid holidays, flexible PTO for salaried employees, and accrued time off for hourly employees
• Comprehensive Health Plans: Medical, Dental, and Vision coverage for full-time employees and their families
• Generous HSA Contribution: Monthly contributions if you choose a High Deductible Health Plan
• Paid Parental Leave: Generous paid leave for all full-time employees
• Family Forming Benefits: Resources and financial support to help build your family
• 401(k) Matching: Contribution matching to invest in your future
• Personal Device Allowance: Tax-free funds for personal device usage
• Pre-tax Benefits: Access to Flexible Spending Accounts (FSA) and Commuter Benefits
• Lifestyle Wallet: Monthly contributions for fitness, professional development, coworking, and more
• Mental Health Support: Dedicated access to therapy and coaching
• Sabbatical Leave: Paid leave after 5 years of employment

Pay

Compensation Range: $250K - $325K, plus competitive equity grants for full-time employees.