Sprinter Health

5 days ago

Applied Scientist, Optimization & Logistics

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Turn complex logistics and scheduling problems into optimization models, forecasting, and simulation to match clinicians to home-care patients under real-world constraints. Build strong baselines, run offline/online evaluations and backtests, and choose metrics for stochastic systems. Partner closely with operations, product, and engineering to productionize decision systems, validate assumptions, and improve outcomes like cost per visit, utilization, access, and completed visits.

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Supply Chain & Logistics

Key Responsibilities

•Convert ambiguous operational problems into optimization, forecasting, or simulation tasks.
•Build and improve baselines efficiently, adding complexity only when justified.
•Develop solutions using operations research, optimization, and machine learning, selecting the right tool for each problem.
•Design offline evaluations, backtests, and live experiments to predict real operational impact, and communicate results to stakeholders.
•Partner with engineering to productionize optimization and decision systems and validate assumptions with operations partners.

Pay and Benefits

Salary: USD 160,000 - 220,000 annually

Perks:EquityHealth InsuranceDentalVision401kPaid LeaveLife InsuranceLearning BudgetMeal Allowance

Key Requirements

•Strong foundations in operations research or optimization, including modeling, algorithms, experimental design, and evaluation.
•Strong Python and SQL, with the ability to run experiments end to end.
•Ability to turn ambiguous problems into well-posed optimization or forecasting tasks and adapt relevant literature to new problems.
•Judgment about uncertainty, constraints, and edge cases in real-world operational data.
•MS or PhD in a quantitative field (operations research, industrial engineering, computer science, applied math, statistics, machine learning), or exceptional equivalent experience.

Experience:Operations researchOptimizationMachine learningHealthcare

Education:Master's in operations research, industrial engineering, computer science, applied math, statistics, machine learning

Skills:Reasoning from first principlesScientific rigorCross-functional communicationProblem-solvingDecision-making under uncertainty

Tech Stack:PythonSQLClaude CodeCursor

Company Brief

Sprinter Health

Operates mobile and home-based primary care services focused on delivering in-home medical visits, chronic care management, and coordinated care for patients who face barriers accessing clinic-based care.

Industry: Healthcare Providers

Website

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Sprinter Health

5 days ago

Applied Scientist, Optimization & Logistics

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 15 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Supply Chain & Logistics

Key Responsibilities

•Convert ambiguous operational problems into optimization, forecasting, or simulation tasks.
•Build and improve baselines efficiently, adding complexity only when justified.
•Develop solutions using operations research, optimization, and machine learning, selecting the right tool for each problem.
•Design offline evaluations, backtests, and live experiments to predict real operational impact, and communicate results to stakeholders.
•Partner with engineering to productionize optimization and decision systems and validate assumptions with operations partners.

Pay and Benefits

Salary: USD 160,000 - 220,000 annually

Perks:EquityHealth InsuranceDentalVision401kPaid LeaveLife InsuranceLearning BudgetMeal Allowance

Key Requirements

•Strong foundations in operations research or optimization, including modeling, algorithms, experimental design, and evaluation.
•Strong Python and SQL, with the ability to run experiments end to end.
•Ability to turn ambiguous problems into well-posed optimization or forecasting tasks and adapt relevant literature to new problems.
•Judgment about uncertainty, constraints, and edge cases in real-world operational data.
•MS or PhD in a quantitative field (operations research, industrial engineering, computer science, applied math, statistics, machine learning), or exceptional equivalent experience.

Experience:Operations researchOptimizationMachine learningHealthcare

Education:Master's in operations research, industrial engineering, computer science, applied math, statistics, machine learning

Skills:Reasoning from first principlesScientific rigorCross-functional communicationProblem-solvingDecision-making under uncertainty

Tech Stack:PythonSQLClaude CodeCursor

Company Brief

Sprinter Health

Industry: Healthcare Providers

Website