NLP Medical Data Scientist

  • Location

    San Francisco

  • Sector:

    Software Engineering, Data Science

  • Job type:


  • Contact:

    Jason Rumney

  • Contact email:


  • Job ref:

    AAJR 30483930

  • Startdate:


  • Consultant:

    Jason Rumney

Our client’s mission is to make the highest quality healthcare available to everyone. We’re building a diagnostic engine that learns from and empowers the world’s most accurate radiologists–but enabling diagnosticians is just the beginning. Through our end-to-end workflow, we’re working to improve the quality and efficiency of the entire episode of care, simplifying the process of medicine and allowing doctors to focus on patients. We are interdisciplinary thinkers who are passionate about technology and medicine, and believe in the power of technology to protect and preserve human life. We’re in stealth mode and hiring!


Medical product data scientists leverage our varied data feeds to quantify, measure and improve efficiency, quality and value in radiological medicine. These data feeds may include natural language, radiological images, application user data, patient outcomes, and billing and insurance information. Example projects range from optimizing radiologist efficiency by understanding user behavior in our applications to uncovering relationships between pathologies implicit in radiology report data. 


  • Advanced degree in a quantitative discipline, or equivalent experience

  • Experience leveraging user data to optimize product features and data science models

  • Expert-level statistics and machine learning

  • Fluency with Python

  • Track record building and productionizing models in an industry setting


  • PhD in a related field or equivalent work experience

  • Experience working with medical and/or radiological data and biomedical ontologies

  • Understanding of modern NLP techniques and applications

  • Understanding of modern computer vision techniques and applications


  • Work on challenging fundamental data science problems in the medical domain

  • Extract behavioral, process and medical insights from messy multimodal data

  • Define efficiency, quality and value metrics as they relate to our various data feeds and the practice of radiology

  • Leverage metrics to continually optimize data science modelsPublish results in academic journals and represent the company at academic and industry association meetings

  • Develop a scalable A/B testing framework and process for evaluating changes to the user experience and features 

  • Drive the collection and curation of new data and the refinement of existing data sources

  • Be a thought leader in value-driven medicine


  • Stock

  • Competitive salaries

  • Paid time off

  • Medical insurance

  • 401(k)

  • Apple equipment

  • Dedicated research computing resources

  • Catered lunches and team events

  • Sponsorship for conferences