Onsite Data Scientist - Optimization & Predictive Modeling

Agri-Beef-Co.; Boise (ID); On-site; USD 110,000 - 160,000; Full time

Job summary

Agri-Beef-Co. seeks a Data Scientist on-site in Boise to apply mathematical optimization and predictive modeling to improve business decisions. You will collaborate with BI, developers, and plant and sales leaders to translate constraints and domain knowledge into trusted models used in daily operations.

Responsibilities include building LP/MIP models, validating with historical data, deploying models, and communicating findings to executives and teams.

Qualifications

• Demonstrated experience formulating and solving optimization problems in a production setting, including infeasibility and performance debugging.
• Hands-on experience with solvers and modeling frameworks (Gurobi, CPLEX, HiGHS, OR-Tools, Pyomo).
• Strong foundation in statistics, probability and experimental design, with good judgment on model simplicity.

Responsibilities

• Formulate, build and maintain optimization models (LP, MIP) for production planning, allocation and scheduling.
• Validate models against historical operations using replay and simulation; tune objectives and constraints.
• Deploy models into production with monitoring, retraining and performance tracking.
• Partner with business leaders to identify problems where optimization, forecasting or classification can improve margins.
• Design, build and validate statistical and machine learning models using enterprise data.
• Communicate findings to non-technical audiences through summaries, visualizations and presentations.
• Establish standards for reproducibility, version control, testing and responsible data use.
• Protect data by following security and privacy policies.

Skills

Optimization

Predictive Modeling

Python

SQL

Power BI

CI/CD

Version Control

Data Visualization

LP/MIP

Gurobi

Tools

Gurobi

CPLEX

HiGHS

OR-Tools

Pyomo

Job description

Agri-Beef-Co. seeks a Data Scientist on-site in Boise to apply mathematical optimization and predictive modeling to improve business decisions. You will collaborate with BI, developers, and plant and sales leaders to translate constraints and domain knowledge into trusted models used in daily operations.

Responsibilities include building LP/MIP models, validating with historical data, deploying models, and communicating findings to executives and teams.