IT Data Scientist

Agri Beef- Real Families, Great People, Exceptional Beef • Boise, ID

13h • Onsite

About The Position

The Data Scientist applies mathematical optimization and predictive modeling to improve how Agri Beef makes 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.

This is an onsite role; remote and hybrid opportunities are unavailable. The position formulates and maintains optimization models for production planning, product allocation, and scheduling; validates models using historical operations, replay, and simulation; and deploys models into production in partnership with the development team. It also identifies opportunities for optimization, forecasting, or classification, develops statistical and machine-learning models, communicates findings to non-technical audiences, supports external research partnerships, establishes reproducible and responsible data practices, and follows company data-security, access, and privacy policies.

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

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 tooling, and 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 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 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