Senior Operations Research Engineer
Location: Remote
Department: Operations Research
About Us
Hungryroot is using AI to build the most consumer-centric food and wellness company to ever exist. We act as your personal assistant for healthy living—getting to know your goals, lifestyle, and budget, and recommending and delivering healthy groceries, easy recipes, and essential supplements for you and your family.
It’s the easiest way to eat healthy, achieve your goals, save time, and discover new foods. We believe food is the foundation of health, convenience should not mean compromise, and that everyone is unique in how they eat and live. That’s why we’re building a future in which healthy living is both easy and enjoyable.
Hungryroot is a distributed team of top talent across 28+ U.S. states. While we have a headquarters in New York City, our remote-first culture emphasizes collaboration, team-building, and flexibility. Expect regular virtual team events, strong ownership and accountability, and an annual company retreat.
About the role
We’re looking for a Senior Operations Research Engineer to be a part of our growing Data Science team. You’ll be responsible for working directly on our core Machine Learning/Operations Research algorithms for: grocery personalization, recipe selection, supply chain forecasting, clustering and more. As a member of the team, you will be building models collaboratively with others, and implement them in experimentation and production settings. You will be analyzing results of experiments, and will deep dive into the results to understand their impact, as well as plan next iterations.
This role will join Hungryroot’s Data Science team and you’ll report directly to our Director of Data Science. In this critical role you will work closely with our data scientists and operation research experts to tackle the core challenges at the company that will be crucial to the success of Hungryroot. If you want to help us change how people grocery shop and eat for the better, we’d love for you to apply!
Responsibilities
- Building out Operations Research modeling for our box filling algorithms, inventory forecasting, supply chain optimization
- Machine learning modeling for our core grocery personalization algorithms
- Data analysis, discussion and interpretation of experiment results
- Data analysis and interpretation of production data to inform future experiments and decisions
Qualifications
- Experience with optimization tools and libraries (Gurobi, CPLEX, PuLP) Gurobi is our primary platform for linear optimization
- Knowledge of Machine Learning algorithms and systems, with at least one application built and deployed to production
- Strong programming skills in Python
- Proficiency in data manipulation, analysis, and visualization.
- Excellent problem-solving skills and the ability to translate business problems into mathematical models.
- Demonstrated ability to work independently and collaboratively in a fast-paced environment.
- Be able to discuss the pros and cons of various solutions to a problem.
- Ability to explain complex technical concepts to non-technical stakeholders.
Nice to Haves
- Machine learning frameworks (e.g., scikit-learn, PyTorch)
- Masters or PhD in Operations Research
Perks & Benefits
- Remote-first: work from home, work from our NYC office, work from anywhere in the U.S. - you decide!
- Equity
- Unlimited vacation policy
- Universal paid parental leave
- Monthly Hungryroot credit for delicious, healthy groceries
- Comprehensive health, vision, dental, and life insurance
- 401k with Company Match
- A work from home stipend to support your initial home-office setup
Expected Salary Range
$168,00-$210,000
#LI-REMOTE
The employer will not sponsor applicants for work visas.
Our mission to help make healthy eating easy, accessible, and joyful is better served by a diverse workplace. We are a proud Equal Opportunity Employer committed to building an inclusive workplace. We have zero-tolerance for harassment or discrimination. We do not discriminate on the basis of any protected class.
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