Senior Data Scientist, Operations Research & Optimization

通用磨坊股份有限公司; United States; Remote; USD 111,000 - 185,000; Full time

Benefits offered by this job

Health benefits

Retirement plan

Time off programs

Wellbeing support

Annual incentive program

Job summary

General Mills is seeking a Senior Data Scientist to advance optimization models, ML solutions, and data-driven decision-making across cross-functional teams. The role emphasizes production-ready analytics, collaboration with product owners, and driving business impact through advanced modeling.

The candidate will apply optimization, simulation, and information retrieval techniques to build scalable analytical engines and mentor colleagues within a collaborative data science environment.

Qualifications

• 5+ years in data science, decision sciences, OR, or related field (PhD candidates may qualify for 3+ years).
• Master’s or PhD in related quantitative field.

Responsibilities

• Develop optimization models and ML solutions with production-ready deployment.
• Provide data science leadership within a product team; deliver actionable insights.
• Design modeling frameworks for deterministic and combinatorial optimization, ML, and related problems.
• Monitor model performance and improve recommendations based on feedback.
• Communicate recommendations clearly to stakeholders and educate teams on data-driven decision making.
• Collaborate with other Data Scientists and product partners on standards and processes.

Skills

SQL

Python

Optimization

Data Visualization

Analytical thinking

Communication

Education

Master’s or PhD in operations research, industrial engineering, computer science, or related field

Tools

Large-scale optimization tools

Job description

General Mills is seeking a Senior Data Scientist to advance optimization models, ML solutions, and data-driven decision-making across cross-functional teams. The role emphasizes production-ready analytics, collaboration with product owners, and driving business impact through advanced modeling.

The candidate will apply optimization, simulation, and information retrieval techniques to build scalable analytical engines and mentor colleagues within a collaborative data science environment.