Director, Data Science
Remote • SF Office • FullTime
Posted 3mo ago
About the job
Abridge is seeking a Director of Data Science to build a world-class data team and implement a comprehensive data strategy that democratizes data in the age of AI. This role is crucial for providing insights, clarity, and speeding up decision-making across the company. The Director will collaborate closely with Product, Engineering, Science, commercial, and finance teams to guide strategic decisions and drive product strategy through data-driven insights.
Responsibilities
- Build and manage a world-class team of data scientists, providing guidance, mentorship, and setting high standards.
- Foster a high-impact, collaborative team culture focused on agency, clarity of thought, and pride in authorship.
- Drive product strategy through data-driven insights across the product portfolio, including user behavior analysis, product performance deep-dives, and causal inference experimentation.
- Partner with product, strategy, and research teams to develop sophisticated ROI frameworks for customers.
- Collaborate with the research team on model evaluation, shaping frameworks, production performance monitoring, 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 with Data Engineering to identify data gaps, ingest data, and prepare it for optimal use.
- Make critical technical infrastructure decisions for the data organization, including tooling, build vs. buy tradeoffs, and setting technical standards.
- Build the data science organization 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, particularly in product-facing roles driving impact through data.
- Depth of experience using Python, R, and SQL for large-scale analytics.
- Comfort building data capabilities from early stages through rapid growth, including interfacing with data engineering and machine learning.
- Experience with data visualization tools, including BI tools (e.g., Tableau, Looker, Sigma) and code-based tools (e.g., Seaborn, ggplot2).
- Excellent communication skills, capable of delivering quantitative findings clearly to non-technical stakeholders.
- Strong leadership skills to build teams, drive urgency, and prioritize effectively in a rapid growth environment.