Senior Data Scientist

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.

Our generative AI-powered products are revolutionizing the practice of medicine, and we’re looking for a highly motivated Senior Data Scientist to join our growing US-based Data Science & BI team. Your work will be instrumental in driving product strategy, directly influencing how healthcare professionals engage with patient data.

Data Analysis and Insight Generation

Extract meaningful insights

identify trends and patterns

relevant to our business and product, by collecting, cleaning, and analyzing internal and external data

Ensure end-to-end visibility and understanding of our AI generation pipelines, from internal quality metrics to automated assessment in production.

Investigate and correct issues identified through data operations monitors, tools, and reports.

Advanced Data Modeling

User Behavior Modeling :

Identify user patterns and insights by analyzing user interactions, engagement metrics, funnel analysis, etc. for product improvement and feature development. It is critical for data to drive increased user engagement and retention.

A / B Testing :

Design and analyze A / B tests to evaluate the effectiveness of product features and design changes.

AI model evaluation :

Design and analyze metrics to evaluate our AI models, guide the team on gaps in evaluation processes, and drive solutions to improve measurable outcomes.

Cross-Functional Leadership and Collaboration

Collaboration with Product Teams :

Work closely with product managers, designers, and engineers to translate data insights into product priorities.

Serve as a domain expert for the business context of our analytics data, sharing your understanding of the assumptions and limitations of our business metrics.

Continually enhance our understanding of the business and product, by identifying and filling gaps in our data sources. This includes working closely with multidisciplinary teams such as product, engineering, partner success, and the executive team.

8+ years using Python, R, SQL for analytics

5+ years in product-facing roles, driving product outcomes through A / B testing, defining aggressive project and company-level goals, and helping teams achieve them.

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

Data Advocate

Excellent communicator capable of effectively delivering quantitative findings to non-technical stakeholders in a clear and compelling fashion.

A team player, comfortable assisting others across the organization in solving data problems and answering questions with data

Ability to prioritize amidst changing priorities in a fast moving environment

Domain-relevant Knowledge

Knowledge of healthcare settings, electronic health records (EHR), and healthcare billing are all a plus

Experience with common approaches to measure and drive user engagement is a plus

Must be willing to work from our SF office at least 3x per week

This position requires a commitment to a hybrid work model, with the expectation of coming into the office a minimum of (3) three times per week.…