Senior Data Scientist, Causal Inference (Hybrid)

About the Role

Key Responsibilities

• Deliver analytic and data science products - from business intelligence to analytics to predictive modeling - within the health care data domain (e.g., clinical outcomes, clinical quality, cost of care)
• Develop novel methodologies to understand and predict our product performance, based on clinical and cost indicators
• Develop risk stratification models using EHR, claims, RA, actuarial experience, and a variety of other data sources to match our members with the appropriate care pathways
• Conduct opportunity assessments for reducing total cost of care or improving code capture as we work in new geographies and with new clients and partners
• Evaluate the effectiveness of service delivery for different population segments relative to clinical and cost outcomes
• Partner with our data engineering team to build a healthcare data infrastructure that supports high-impact analytics

Requirements

• 5+ years of hands-on health care analytics, actuarial, or data science experience
• Strong technical skills necessary to perform advanced analytics: coding (e.g., R, Python, Scala), experience with data management (DBT) and visualization tools (e.g., SQL, Tableau, Looker, Metabase, open source platforms), and experience performing machine-learned analysis with large datasets
• Deep experience with clinical and/or claims data, especially Medicare data
• Experience building scalable code that follows engineering best practices
• A collaborative approach to working with stakeholders to help define the question, shape the analysis plan, and deliver and interpret results or models
• Ability to dive deep into details and zoom out to see the big picture
• Previous experience developing risk stratification models with a variety of healthcare data sources
• Creative problem solving, curiosity and the drive to learn new methods

Nice to Have

• Experience with value-based care analytics and data science
• Experience with the TUVA Project
• Experience working on a small, fast-paced team
• Strong foundation in probability & statistics, demonstrated expertise with ML tools, SQL, Python, and statistical & ML packages
• Experience empowering teammates' work via mentorship, coaching, synchronous & asynchronous code review, and leading by empathy and example

Qualifications

• Not explicitly specified; implied: relevant experience in health care analytics, actuarial, or data science roles

Benefits & Perks

• Competitive salary, equity grant, generous paid time off
• Comprehensive benefits package including medical, dental & vision insurance with 100% of monthly premium covered for employees
• Company-sponsored 401k plan
• Flexible working arrangement