Data Scientist (People Analytics & Optimization)
Remote (U.S. based)
Full-Time | Direct Hire | Healthcare | Optimization + ML
A leading national provider of community-based healthcare is building its People Analytics and Optimization team. With over 2,000 facilities and a mission to improve care delivery across a distributed network, this organization is investing in advanced data science to improve staffing, scheduling, and workforce logistics.
We're hiring a Data Scientist with experience in operations research, optimization modeling, and applied machine learning to help model real-world labor and logistics challenges across a complex care ecosystem.

What You'll Do:

Build and deploy optimization models (linear, integer, MIP) for workforce planning
Develop algorithms using tools like Pyomo, OR-Tools, Gurobi, SciPy
Analyze large-scale operational and regulatory datasets across thousands of sites
Collaborate with teams across operations, HR, and IT to turn challenges into algorithms
Simulate real-world constraints for staffing, licensing, and compliance
Communicate findings and recommendations to both technical and executive audiences

What We're Looking For:

3+ years in data science, operations research, or applied optimization
Proficiency in Python (NumPy, pandas, Pyomo, PuLP, Gurobi, etc.)
Experience designing objective functions in constraint-heavy environments
Familiarity with workforce logistics, scheduling, or supply chain problems
Strong communication skills-comfortable bridging technical and non-technical teams
Advanced degree in OR, Industrial Engineering, or Applied Math preferred

Nice-to-Haves:

Experience with healthcare, especially distributed care systems
Exposure to HR analytics or building decision-support tools for workforce planning
Familiarity with internal dashboarding or simulation tooling