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Lead Data Scientist, Demand

Farmer's Fridge Careers Chicago, IL

Chicago, IL

Today

$160k - $170k/yr Full time Data Science Data Science Ops Data Scientist

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Job Description

Farmer’s Fridge Careers is hiring a Lead Data Scientist, Demand to own and continually improve demand planning forecasting models used to determine how much fresh food to send to each fridge and retail store. This role drives end-to-end forecasting work, from data and feature development through model validation, production deployment, and performance monitoring, with an emphasis on outcomes that support contribution margin.

The models you improve will forecast item, location, and day-level demand across 2,000+ fridges and retail partner stores, where demand can be low-volume and intermittent. You will focus on modeling the complexities of fresh food, producing probabilistic forecasts that inform optimization tradeoffs between lost sales and waste, and partnering closely with decision science, planning, supply chain, and data engineering.

What you’ll own

End-to-end ownership of fridge and retail demand forecasts, including data, features, model, validation, and production.
Forecasts designed to maximize contribution margin dollars, using business outcome tracking rather than accuracy alone.
Ongoing maintenance and improvement of production models, including rebuilding models when a better approach clearly delivers value.
Forecasting at the item, location, and day level across 2,000+ fridges and retail partner stores.
Modeling key fresh-food drivers such as stockouts that hide true demand, short shelf life, new fridge ramp-up, new menu items, holidays, and promotions.
Production-ready probabilistic forecasts so optimization can weigh the cost of lost sales against the cost of waste.
Backtesting and monitoring, with evaluation grounded in business outcomes like sell-through, unsolds, and stockouts.
A standing model scorecard reviewed on a set cadence with Channel Strategy and Demand Planning.
Partnering with Data Engineering to run models in production pipelines using Snowflake, dbt, and Dagster without manual babysitting.
Measuring and incorporating the value of planner overrides by promoting consistently helpful overrides into explicit model rules and retiring the rest.
Maintaining a living record of every business rule in the models, including ownership and last change date.
Raising the bar for how forecasting models get built, tested, documented, and shipped at Farmer’s Fridge.

How you’ll collaborate

Work with the Lead Decision Scientist to deliver the forecast outputs the solver needs, and measure how forecast changes shift stocking decisions and results.
Coordinate with demand planning, supply chain, and operations to explain model expectations, rationale, and how much to trust the outputs.
Set up measured “before and after” evaluations for material model changes, translating impact into contribution margin per fridge per week.
Expand forecasting beyond channel demand into company-level volume and revenue forecasting as the core models mature.

Requirements

4-8 years building and maintaining forecasting or predictive models in production.
Deep demand forecasting experience using time series, hierarchical, or ML-based methods (for example: gradient boosting, state space, Bayesian, or similar).
Comfort with count data and intermittent demand (for example: Poisson, negative binomial, or similar).
Experience correcting for censored demand from stockouts, or strong understanding of why it matters.
Strong Python and SQL, with experience using Snowflake or a similar cloud data warehouse.
Rigor in backtesting and experiment design, including the ability to prove a model change improved outcomes.
Track record owning model work end to end, from framing through production and monitoring.
Ability to tie a shipped model change to a business result, in dollars.
Clear communication to explain forecast uncertainty and tradeoffs to planners and operators, and defend modeling choices to technical peers.
Comfort operating in a fast-paced environment with ownership of direction.
Familiarity with using AI tools in day-to-day workflow.
Based in Chicago or willing to relocate; this is an in-office role.

Technology

Python
SQL
Snowflake
dbt
Dagster

Compensation and benefits

Salary: USD 160,000 - 170,000 per year
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)
Company performance-based bonuses
Equity

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