iO Associates
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
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