Data Scientist, Particle Health

• The team works in-office two days per week (Tuesdays and Thursdays), so applicants should be within commuting distance and comfortable with in-person collaboration
• 3+ years in data science, analytics, or a related role
• Proficiency in Python and SQL skills
• Experience working with or strong interest in healthcare data (EHR, FHIR, HL7, claims)
• Experience developing analytical models or applying statistical methods to solve business problems
• Exposure to modern AI methods, such as generative models, large language models (LLMs), or applied AI systems, and understanding how to integrate them into analytical workflows
• Experience with data visualization / BI tools (e.g., Looker, Tableau, or Dash)
• Exposure to machine learning concepts and model evaluation
• Curiosity, problem-solving mindset, strong communication, proactive learner

Desirable

• As a Data Scientist, you’ll play a key role in helping us analyze healthcare data and generate insights that enable our customers to deliver better patient outcomes
• You’ll work with diverse datasets — including EHR, prescription, and provider data — to build models, surface trends, and help turn complex healthcare data into actionable intelligence. This is a great opportunity for someone who’s excited to apply analytical and technical skills to real-world healthcare problems and grow within a mission-driven team
• You’ll collaborate closely with data engineers, product managers, and software engineers to design analytical products, improve data quality, and explore ways to make our data more valuable to both internal teams and customers
• Build and validate analytical and machine learning models to address key healthcare data challenges (e.g., treatment adherence, gaps in care, risk scoring)
• Explore, clean, and analyze large-scale healthcare datasets to identify patterns and generate actionable insights
• Work with Product and Engineering to translate findings into scalable, production-ready solutions
• Contribute to projects involving AI and NLP, helping extract and summarize meaningful information from clinical text
• Ensure statistical rigor, accuracy, and reproducibility in all analyses
• Identify and address data quality gaps to improve completeness and reliability
• Partner with the Data Engineering team to enhance the usability and consistency of our datasets
• Develop dashboards and metrics that help internal teams and customers better understand our data
• Work cross-functionally with Product, Engineering, and Data teams to align on goals and deliver data-driven insights
• Communicate findings clearly to both technical and non-technical audiences
• Continuously learn, experiment, and contribute ideas to improve how we use data to drive outcomes