IT Data Scientist

Agri Beef

Boise, IDOn-siteFull time
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Location
Boise, ID
Work style
On-site
Job type
Full time
Posted
Nov 3
2 days ago
Career path

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About the company

Agri Beef

Food production · 1,001 to 5,000 employees

Agri Beef on LinkedIn

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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See full description on company page, apply now

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

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