Senior Data Scientist

通用磨坊股份有限公司•Minneapolis, MN

8d•$110,800 - $184,800

About The Position

We are hiring a Senior Data Scientist to help shape the next generation of advanced analytics and AI solutions across the enterprise. In this role, you will partner with business stakeholders, product owners, and technical teams to identify high-value opportunities, develop scalable machine learning solutions, and build reusable frameworks that strengthen how data science work gets done across General Mills. This is an exciting opportunity for someone who enjoys both building and influencing: building models, frameworks, and AI-enabled solutions, while also helping teams make smarter, faster, data-driven decisions.

Requirements

5+ years of experience in data science, decision sciences, or a related quantitative field
Bachelor's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field
Strong foundation in machine learning, statistical thinking, and/or analytical problem-solving
Strong proficiency in Python and SQL
Experience working with complex databases and modern data science tooling
Ability to spot questionable data, investigate issues, and improve the overall solution
Strong communication and stakeholder management skills, with the ability to translate business needs into technical solutions
Experience with cloud platforms such as GCP or similar environments
Candidates must be currently authorized to work in the United States on a full-time basis

Nice To Haves

Master's degree in Data Science, Computer Science, Engineering, Mathematics, Statistics, or a related field
Experience building large-scale AI or machine learning models
Some experience building AI solutions, including hands-on work with newer AI or agentic capabilities using Python or a similar programming language
Experience in operational or commercial business environments
Exposure to machine learning engineering practices and coding standards that support scalable, production-minded solutions
A balance of deep data science expertise and practical engineering exposure
Curiosity about where AI can create value and the discipline to prioritize the right use cases
Confidence working with ambiguity and shaping structure where it does not yet exist
A collaborative mindset and the ability to influence across technical and non-technical stakeholders

Responsibilities

Partner with data science leaders, AI engineering teams, and business stakeholders to identify, prioritize, and deliver high-impact AI and machine learning use cases
Design, prototype, and scale advanced analytics and AI solutions using best-in-class tools and technologies
Frame business problems as measurable data science opportunities and translate them into practical, value-focused solutions
Build production-ready, reusable, and scalable models that generate timely, actionable insights
Work across semi-structured data use cases, including problem framing, data curation, model development, and evaluation
Monitor model performance, incorporate stakeholder feedback, and continuously improve solution effectiveness
Help define and standardize data science ways of working, including common processes, reusable assets, frameworks, and best practices
Communicate recommendations clearly and persuasively, helping partners understand the why behind the work and trust the path forward
Contribute to a strong team culture by collaborating, sharing ideas, asking questions, and supporting other data scientists