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Staff ML Data Scientist

New York, New York, United States

About CookUnity

Food has lost its soul to modern convenience. And with it, has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 35 million meals a year from the industry’s best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul.

Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world.

If that mission has you hungry in more ways than one, you’ve found the right job posting.

About the role:

We’re looking for an experienced ML-focused Data Scientist to design, build, and productionize personalization and recommendation systems that help every CookUnity customer discover meals they’ll love. You’ll develop user modeling and ranking algorithms, ensure they integrate seamlessly into production, and lead experimentation strategies to measure their real-world impact. This is a hands-on, high-impact role for someone who can blend strong machine learning expertise with strategic thinking, rigorous experimentation, and close collaboration with Product, Engineering, and Business stakeholders.
 
What You’ll Do
 As a Staff level Machine Learning–savvy Data Scientist at CookUnity, you'll:
  • Architect and deliver production-grade recommendation and personalization systems, from user modeling to ranking algorithms and embeddings.
  • Quantify and optimize business impact through A/B testing, experimentation design, causal inference, and lift analyses.
  • Translate product and business needs into effective, data-driven solutions that scale.
  • Collaborate with cross-functional teams to embed experimentation and feedback loops into our workflows.
  • Mentor and coach the data team on best practices in ML model validation, experimentation, and scalability.
You Might Be a Great Fit If You Have:
  • 6+ years in data science, machine learning, or applied statistics.
  • Deep experience building recommendation engines, personalization pipelines, ranking/relevance models, search optimization, or embedding-based features.
  • Hands-on familiarity with A/B testing frameworks, and skills in experimentation design, causal inference, and measuring incremental impact.
  • Strong programming chops in Python and SQL (with bonuses for experience in Snowflake, PyTorch, Airflow, MLFlow, ECS)
  • A proven ability to work across disciplines and guide stakeholders—while also owning the technical end-to-end performance of your models.
  • Bonus if you’ve worked in marketplaces, subscription services, food-tech, or adjacent domains.

Benefits

🩺  Health Insurance coverage

🌅 401k Plan

⛱ Unlimited PTO 

🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical

🐣 Paid Family leave

🕯 Compassionate Leave: 3-5 days each time the need arises

🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly

🧘🏽‍♀️ Wellness perks: access to a nutritional coach and fitness subsidies to build a healthy lifestyle

👩🏾‍🏫 Personalized Spanish coach

🌟 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!

 

 

Compensation

All final pay rates will be determined by candidates experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.

Pay Range for this position

$190,000 - $200,000 USD

 

If you’re interested in this role, please submit your application and if we think you might be a fit, we'll get in touch with you. Thank you for your time!

CookUnity is an Equal Opportunity Employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability.

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