DATA SCIENTIST HORMEL FOODS - (AUSTIN, MN/EDEN PRAIRIE, MN)
To save time applying, Hormel Foods does not offer sponsorship of job applicants for employment-based visas for this position at this time.
ABOUT HORMEL FOODS - Inspired People. Inspired Food.
Hormel Foods Corporation, based in Austin, Minnesota, is a global branded food company with approximately $12 billion in annual revenue across more than 80 countries worldwide. Its brands include Planters®, Skippy®, SPAM®, Hormel® Natural Choice®, Applegate®, Justin's®, Wholly®, Hormel® Black Label®, Columbus®, Jennie-O® and more than 30 other beloved brands. The company is a member of the S&P 500 Index and the S&P 500 Dividend Aristocrats, was named one of the best companies to work for by U.S. News & World Report, one of America's most responsible companies by Newsweek, recognized by TIME magazine as one of the World's Best Companies, and has received numerous other awards and accolades for its corporate responsibility and community service efforts. The company lives by its purpose statement - Inspired People. Inspired Food. - to bring some of the world's most trusted and iconic brands to tables across the globe. For more information, visit www.hormelfoods.com .
Summary
Hormel Foods is seeking a Data Scientist who can translate real business needs into production-grade AI/ML and LLM-powered systems. This role is responsible for building end-to-end AI services that directly support planning, forecasting, optimization, quality, logistics, and other critical workflows-driving measurable operational value.
You will partner closely with business stakeholders to define outcomes, integrate solutions into real processes, instrument KPIs, and iterate rapidly in production. Success in this role means not just developing models, but shipping AI products that deliver tangible, ongoing results.
What You'll Do
Deliver Business Value Through AI
Translate high-value business problems into production AI services with clear KPIs (e.g., OTIF, planner productivity, cycle-time, waste reduction).
Co-design workflow integrations with business teams to ensure adoption and measurable value-not just model accuracy.
Identify and prioritize high-ROI opportunities in partnership with business leaders.
Build & Ship Production AI Systems
Design, implement, and deploy AI/ML and LLM-backed services (APIs, batch/stream pipelines, event-driven automations) in a cloud-native environment.
Develop predictive and prescriptive capabilities (e.g., demand signals, inventory positioning, lead-time risk) that drive automated or human-in-the-loop decisions.
Build and harden REST APIs and corresponding lightweight front-end UIs (e.g., Streamlit) to support business workflows.
Containerize services (Docker) and orchestrate deployment using Kubernetes or serverless, with automated CI/CD and infrastructure-as-code.
Coach peers on best practices in design, code quality, and secure-by-default engineering.
Core Tech Stack (you don't need all, but you're fluent in many)
Languages/Frameworks: Python, SQL, FastAPI
GenAI & LLM: LangChain, Google ADK, OpenAI Agents, embeddings
ML Platform: scikit-learn, XGBoost/LightGBM, Vertex AI
Data & Orchestration: Cloud ecosystem such as GCP, AWS, or Azure
Infra/MLOps: Docker, CI/CD, GitHub
Responsibilities (Day-to-Day)
Lead end-to-end delivery of AI services: design ? build ? test ? deploy ? observe ? iterate
Build and harden REST APIs and corresponding front-end Web UIs (e.g.Streamlit)
Implement evaluation harnesses for LLMs (quality, safety, hallucination, cost/latency) and ML (offline & online metrics)
Instrument business impact and operational KPIs; build dashboards for system health and value realization
Coach peers on best practices, code quality, and secure-by-default patterns
Collaborate with business leaders to identify the highest-ROI opportunities
QUALIFICATIONS:
Required
Bachelor's in a quantitative field (CS, Engineering, Math/Stats, OR, Economics) or equivalent experience
3+ years building and operating production ML/AI services, including APIs, CI/CD, and cloud deployment
Strong Python and SQL skills; experience with Docker and at least one major cloud provider
Hands-on experience with LLMs
Demonstrated ability to partner with non-technical stakeholders and deliver measurable outcomes
Applicants must not now, or at any time in the future, require employer sponsorship for a work visa.
Applicants must be authorized to work in the United States for any employer.
Preferred
Experience with Vertex AI (BigQuery, Vertex endpoints) or similar managed ML platforms
Familiarity with AI governance frameworks
Master's degree or P.H.D. in a quantitative field
LOCATION:
Austin, MN - Global Headquarters (preferred); Eden Prairie, MN (office location)
TRAVEL REQUIREMENTS: Travel may be necessary 10% of the time.
BENEFITS: Hormel Foods offers an excellent benefits package. Competitive base salary plus bonus, annual merit increase performance reviews, medical, dental, vision, non-contributory pension, profit sharing, 401(k), stock purchase plan, relocation assistance, paid vacation.
The base pay range for this position $98,100-$137,300 per year; however, actual compensation is influenced by a wide array of factors including but not limited to job-related knowledge, skills set, level of experience, and specific office location.
At Hormel we invite difference and diversity in all aspects. We offer a space of support, understanding, and community. We are committed to the journey! Learn more about our progress here: https://www.hormelfoods.com/about/diversity-and-inclusion/
Hormel Foods provides equal employment opportunities to applicants and employees without regard to race; color; sex; gender identity; sexual orientation; religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.
Requisition ID : 33000
Hormel Foods Corporation is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, gender, sexual orientation, gender identity, national origin, disability, or veteran status.
