About this Role: This is a new discipline for Farmer's Fridge. We're introducing optimization and decision science as its own capability - distinct from our existing data science and forecasting work - and you'd be the first person to own it. We already have a route optimization and inventory allocation model live in NextMV; your job is to take that from built to fully rolled out, and then build the next models that turn our supply chain planning process into something we solve with math instead of manual judgment.
You'll work alongside other members of the data team, including a data scientist - you own the solver and the prescriptive layer that acts on model inputs like demand forecasts. Real ownership, and the latitude to define how this discipline gets built at FF.
What You'll Do...
- Own the solver stack (Gurobi) - model formulation standards, performance, and validation.
- Take our existing route optimization and inventory allocation model from built to rolled out, partnering with planning and ops stakeholders to define success benchmarks and rollout criteria.
- Build new decision models across the supply chain planning process - inventory, production, fulfillment, and network decisions - wherever we're running on manual planning or heuristics today.
- Work in the NextMV platform to develop, test, and deploy optimization models into production.
- Translate ambiguous planning problems - constraints, tradeoffs, objectives - into solvable mathematical formulations.
- Partner with the data science team on model inputs (demand forecasts, feature data) without owning the predictive layer yourself.
- Communicate model logic, tradeoffs, and results in plain language to non-technical planning and operations stakeholders - you'll be explaining why the solver made a decision as often as you're building it.
- Write production-quality Python and SQL, and pick up additional languages or tools as the solver environment requires.
- Set the technical bar for how decision science work gets built, tested, and documented at FF - you're establishing the standard, not inheriting one.
Who You Are...
- 4-10 years of experience building decision science or optimization models in a production environment.
- Hands-on experience with mathematical solvers (Gurobi, FICO Xpress, CPLEX, OR-Tools, or similar).
- Experience with the NextMV platform, or the ability to ramp quickly on it.
- Strong Python and SQL skills; comfortable picking up additional languages as the work requires.
- Experience formulating real business problems as linear programs, mixed-integer programs, or constraint satisfaction problems.
- Excellent communication skills - able to explain model tradeoffs to non-technical stakeholders and defend modeling decisions to technical peers.
- Track record as an individual contributor who owns modeling work end-to-end, from formulation through production.
- Comfortable in a fast-paced, ambiguous environment with limited existing precedent - this role is defining the discipline, not joining an established one.
- Familiarity with using AI tools in your day-to-day workflow.
- Based in Chicago or willing to relocate. This is an in-office role.
- Nice to have: experience with supply chain or logistics optimization specifically (routing, inventory, network design); familiarity with dbt/Snowflake; exposure to how optimization models get productionized alongside data engineering pipelines.
The base salary range for this role is $165,000 - $175,000. The base pay offered will be determined by factors such as experience, skills, training, certifications, education, and any applicable minimum wage requirements.
In addition to base salary, this position is eligible for company performance-based bonuses and equity.
We provide a comprehensive benefits package, including:
- Medical, dental, and vision insurance (multiple plans available)
- 401(k) with immediate employer match vesting
- Paid time off (including vacation, sick leave, and holidays)
- Paid sabbatical after 5 years of service
- Employee discounts
- Employee Assistance Program (EAP)
