IT Data Scientist

Agri Beef • Boise, ID

1d • Onsite

About The Position

This is an onsite role; remote or hybrid opportunities are unavailable. The Data Scientist applies mathematical optimization and predictive modeling to improve Agri Beef’s business decisions. The role identifies decisions that can be improved with data, builds supporting models, and brings those models into daily operational use. Working with the Business Intelligence team, developers, and plant and sales leaders, the Data Scientist translates business constraints and domain knowledge into models that are adopted and trusted. Success is measured by business outcomes.

Requirements

• Strong foundation in statistics, probability, and experimental design, with the judgment to determine when a simple model is appropriate.
• Proficiency in Python and advanced SQL; comfortable working directly against a SQL Server data warehouse.
• Ability to explain technical work plainly to executives, plant leadership, and sales teams.

Nice To Haves

• Demonstrated experience formulating and solving optimization problems in a production setting, including infeasibility and performance debugging.
• Hands-on experience with commercial or open-source solvers and modeling frameworks such as Gurobi, CPLEX, HiGHS, OR-Tools, Pyomo, or similar.
• Experience taking models from notebook to production, including CI/CD and source control.
• Familiarity with Power BI or similar tools and with tabular semantic models.

Responsibilities

• Formulate, build, and maintain mathematical optimization models, including LP, MIP, and related methods, for production planning, product allocation, and scheduling.
• Validate models against historical operations using replay and simulation tools; tune objectives and constraints with the planning team until results are trusted.
• Deploy models into production with the development team, including monitoring, retraining, and performance tracking.
• Partner with business leaders to identify additional problems where optimization, forecasting, or classification can improve margin, yield, or customer outcomes.
• Design, build, and validate statistical and machine learning models using data from the enterprise data warehouse and operational systems.
• Communicate findings and model behavior clearly to non-technical audiences through written summaries, visualizations, and presentations.
• Serve as the technical liaison for external research partnerships, translating academic work into models the business can use.
• Establish and follow standards for reproducibility, version control, testing, and responsible use of data.
• Protect company data by following security, access, and privacy policies in every project.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed