IT Data Scientist
Agri Beef
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- Location
- Boise, ID
- Work style
- On-site
- Job type
- Full time
- Posted
- Nov 3
- 2 days ago
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Career path
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About the company
Agri Beef
Food production · 1,001 to 5,000 employees
What you'll do
- Formulate, build and maintain mathematical optimization models for production planning, allocation and scheduling
- Validate models against historical operations using replay and simulation tooling
- Deploy models into production with the development team, including monitoring and retraining
- Partner with business leaders to identify problems where models can improve outcomes
- Design, build and validate statistical and machine learning models
- Serve as the technical liaison for external research partnerships
- Establish and follow standards for reproducibility, version control, testing and responsible data use
What you need
- Demonstrated experience formulating and solving optimization problems in a production setting (preferred)
- Hands-on experience with commercial or open-source solvers and modeling frameworks (preferred)
- Strong foundation in statistics, probability and experimental design (preferred)
- Proficiency in Python and advanced SQL; comfortable working against a SQL Server data warehouse (preferred)
- Experience taking models from notebook to production, including CI/CD and source control (preferred)
- Familiarity with Power BI or similar tools and tabular semantic models (preferred)
- Ability to explain technical work plainly to executives, plant leadership and sales teams (preferred)
Key skills
mathematical optimizationpredictive modelingGurobiCPLEXHiGHSOR-ToolsPyomostatisticsprobabilityexperimental designPythonadvanced SQLSQL ServerCI/CDsource control
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Read the full posting here
Position Purpose: THIS IS AN ON SITE ROLE, REMOTE OR HYBRID OPPORTUNITIES ARE UNAVAILABLE
The Data Scientist applies mathematical optimization and predictive modeling to improve how Agri Beef makes business decisions. The role identifies decisions that can be made better with data, builds the models to support them, and sees those models through to daily use in operations. It works with the Business Intelligence team, developers and plant and sales leaders to turn business constraints and domain knowledge into models that are adopted and trusted. Success is measured by business outcomes.
Essential Duties and Responsibilities
Formulate, build and maintain mathematical optimization models (LP, MIP and related methods) for production planning, product allocation and scheduling
Validate models against historical operations using replay and simulation tooling; 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 further 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
Preferred Qualifications
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 (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; comfortable 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