Applied Scientist, Optimization & Logistics
Applied Scientist building optimization, forecasting, and simulation models to solve complex logistics and clinician-patient matching problems for in-home healthcare delivery. Requires strong operations research foundations, Python/SQL/ML expertise, and experience shipping production decision systems.
About the job
What you will do
Modeling & Optimization
- Turn ambiguous operational problems into well-posed optimization, forecasting, or simulation tasks.
- Build strong baselines and improve on them efficiently, adding complexity only when the value justifies it.
- Develop solutions across operations research, optimization, and machine learning, choosing the right tool for the problem.
- Run careful analysis and iterate toward decisions that improve real operational outcomes — cost per visit, clinician utilization, patient access, and visits completed.
Evaluation & Scientific Rigor
- Design offline evaluations, simulated backtests, and live experiments that predict real-world operational impact.
- Find the gaps between a model’s assumptions and messy operational reality before they reach production.
- Choose metrics suited to stochastic, constrained, and partially observed operational systems.
- Interpret and communicate results effectively to cross-functional stakeholders.
Collaboration & Delivery
- Partner with Engineering to productionize optimization and decision systems reliably.
- Work with operations partners and SMEs to validate assumptions and review where decisions break down.
- Explain tradeoffs, uncertainty, and limitations clearly to product and leadership.
What you have done
- Strong foundations in operations research or optimization: modeling, algorithms, experimental design, and honest evaluation.
- Strong Python and SQL, the standard optimization and ML libraries, and the ability to run your own experiments end to end.
- Fluency with AI coding assistants (e.g., Claude Code, Cursor) in your day-to-day development workflow.
- Ability to turn an ambiguous problem into a well-posed optimization or forecasting task, discover and analyze related literature, and adapt/apply those methods to our tasks.
- Judgment about how uncertainty, constraints, and edge cases behave in real-world operational data.
- Interest in operations collaboration and applied healthcare impact.
What gives you an edge
- MS or PhD in operations research, industrial engineering, computer science, applied math, statistics, machine learning, or a related quantitative field; exceptional applied experience can substitute.
- Depth in a relevant area such as vehicle routing, scheduling, stochastic optimization, discrete-event simulation, queueing, or demand forecasting.
- Experience shipping optimization or decision systems that reached production and had material real-world impact.
- Hands-on experience with supply-and-demand matching in a marketplace, dispatch, or field-operations setting.
- Fluency deciding when an exact optimization approach beats a heuristic or learned one, and vice versa.
What we offer
- Meaningful pre-IPO equity
- Medical, dental, and vision plans 100% paid for you and your dependents
- Flexible PTO + 10 paid holidays per year
- 401(k) with match
- 16-week parental leave policy for birthing parent, 8 weeks for all other parents
- HSA + FSA contributions
- Life insurance, plus short and long-term disability coverage
- Free daily lunch in-office
- Annual learning stipend
Skills
Python, SQL, Operations Research, Optimization, Machine Learning, Vehicle Routing, Scheduling, Stochastic Optimization, Demand Forecasting, Simulation
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