Senior Manager, Data Science

Abridge · Vertical AI · San Francisco, CA · Operations

This role is for a Senior Manager of Data Science at Abridge, a healthcare AI company. The manager will build and lead a data science team, implement data strategy, and drive product strategy using data-driven insights. Key responsibilities include team management, fostering culture, driving product strategy through analysis, partnering with product/strategy/research teams, collaborating on model evaluation, communicating insights, structuring data strategy with Data Engineering, making technical infrastructure decisions, and leveraging AI for data ingestion and insight generation. The role requires an MS/PhD in a quantitative field, 12+ years of experience, strong Python/R/SQL skills, experience building data capabilities, and data visualization tool proficiency. Healthcare experience is a bonus.

What you'd actually do

  1. Build and manage a world-class team of data scientists, providing guidance, mentorship and high standards while growing the team
  2. Foster a high impact and collaborative team culture, focused on having agency, providing clarity of thinking to the organization and pride in authorship
  3. Drive product strategy through data-driven insights across our growing product portfolio, including user behavior analysis, deep-dives into product performance metrics, causal inference experimentation
  4. Partner with our product, strategy, and research teams to develop sophisticated ROI frameworks for our customers, ingesting real-time data and demonstrating impact
  5. 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

Skills

Required

  • 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)
  • Excellent communicator capable of effectively delivering quantitative findings to non-technical stakeholders in a clear and compelling fashion.
  • A strong leader who is able to help build great teams, drive urgency in execution while ensuring we prioritize appropriately in a rapid growth environment

Nice to have

  • Knowledge of healthcare settings, electronic health records (EHR), and healthcare billing
  • Experience diving into / shaping Analytics Engineering (recruiting & supporting)

What the JD emphasized

  • responsible deployment of AI
  • high-agency
  • strong taste
  • high impact
  • speeding up decision making
  • ROI frameworks
  • model evaluation
  • production performance monitoring
  • quality metrics that matter clinically
  • data strategy
  • technical infrastructure decisions
  • speed up data ingestion and insight generation
  • product-facing roles where you had to drive impact by using data to shape product strategy, goal setting and execution
  • building data capabilities from the earliest stages through rapid growth
  • extreme ownership

Other signals

  • AI-powered platform
  • generative AI for healthcare
  • responsible deployment of AI
  • data strategy
  • democratize data in the age of AI
  • AI to speed up data ingestion and insight generation