Senior Data Scientist - Remote: Generative AI & ML

General Mills; Minneapolis (MN); Remote; USD 111,000 - 185,000; Full time

Job summary

General Mills is seeking a Senior Data Scientist to design, prototype, and build next‑generation analytics engines that apply machine learning, data mining, and information retrieval to business decisions. You will collaborate with product owners and business partners to translate needs into measurable outcomes and develop models that reflect real-world decisions.

You will advance Agentic AI, RAG workflows, and LLM fine-tuning while ensuring robust monitoring and continuous improvement of model

Qualifications

• Bachelor’s degree in data science, Computer Science, Engineering, Math, Statistics or other related fields.
• 6+ years of relevant experience with at least 2 years of relevant experience in Data Science.
• Strong foundation of statistical reasoning and critical thinking, with a proven track record of effectively finding solutions to stakeholder problem statements.
• Experience with Python, including some exposure to package development and foundational programming principles.
• Some experience with generative AI concepts, including embeddings, LLMs, agents, and RAG.
• Experience writing complex SQL queries.
• Understanding data warehousing and complex databases.
• Experience with machine learning and data visualization tools.
• Number sense, ability to identify questionable data, dig in and address it.
• Strong communication and collaboration skills to understand business needs, frame problems in familiar language (without compromising statistical fidelity), and present solutions that clearly translate to business value.

Responsibilities

• Design & implementation of AI solutions for semi-structured data, covering problem framing, data curation, and evaluation across classification, entity extraction & summarization.
• Develop high‑quality Agentic AI and RAG workflows, optimizing ingestion, chunking, embeddings, and vector indexing with established frameworks and stores to maximize retrieval performance.
• Technically evaluate novel technology to help inform on the best effort/improvement tradeoffs.
• Quickly learn and iterate with novel technologies/procedures, particularly but not exclusively around generative AI.
• Responsible for monitoring and improvement of model performance metrics and recommendations with feedback incorporated from business partners.
• Implement appropriate generative AI techniques and technologies to solve business problems, including prompt and LLM fine-tuning, RAG, agentic workflows, and tool designs.
• Help business stakeholders translate their objectives into measurable outcomes.
• Apply critical thinking to frame business needs into statistical problems and develop solutions that balance technical completeness/complexity and timely value delivery.
• Be a storyteller to explain the ‘why and how’ of your recommendations to build trust in your solutions.
• Have passion to advocate and educate on the value and importance of data-driven decision-making and analytical methods.
• Identify and develop long-term data science processes, frameworks, tools, and standards.
• Be a part of the team, collaborate, ask questions, engage, and solicit feedback from other Data Scientists.

Skills

Python

SQL

Statistics

Communication

Problem solving

Education

Bachelor’s degree in data science, Computer Science, Engineering, Math, Statistics or other related fields

Master’s degree in data science, Computer Science, Engineering, Math, or Statistics

Tools

Google Cloud Platform

Job description

General Mills is seeking a Senior Data Scientist to design, prototype, and build next‑generation analytics engines that apply machine learning, data mining, and information retrieval to business decisions. You will collaborate with product owners and business partners to translate needs into measurable outcomes and develop models that reflect real-world decisions.

You will advance Agentic AI, RAG workflows, and LLM fine-tuning while ensuring robust monitoring and continuous improvement of model