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Data Science Manager Jobs in Minnesota (NOW HIRING)

The Data Scientist will be responsible for supporting the Global R&D Sciences team to design ... management. What you'll bring: * Engineering or Science background with strong statistical mind set

The Data Scientist will be responsible for supporting the Global R&D Sciences team to design ... management. What you'll bring: * Engineering or Science background with strong statistical mind set

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a ... Experience in fraud detection, cybersecurity, investigations, digital identity, or risk management.

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Data Science Manager information

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$30.4K

$95.1K

$168.5K

How much do data science manager jobs pay per year?

As of Jul 25, 2026, the average yearly pay for data science manager in Minnesota is $95,145.00, according to ZipRecruiter salary data. Most workers in this role earn between $64,600.00 and $122,900.00 per year, depending on experience, location, and employer.

What are the primary responsibilities of a Data Science Manager on a day-to-day basis?

As a Data Science Manager, your daily responsibilities typically include overseeing a team of data scientists and analysts, setting project priorities, and ensuring the timely delivery of data-driven solutions. You will often collaborate with cross-functional teams, such as engineering, product, and business stakeholders, to define problems, scope solutions, and communicate analytical insights. Your role also involves mentoring team members, reviewing code and analysis, and driving best practices in data science methodologies. This position requires balancing technical project oversight with team leadership and strategic business alignment.

What is a Data Science Manager job?

A Data Science Manager leads a team of data scientists to develop and implement data-driven solutions for business challenges. They oversee project timelines, ensure the quality of data analysis, and collaborate with cross-functional teams to drive decision-making. In addition to technical expertise, they require strong leadership, communication, and strategic thinking skills. Their role bridges the gap between data science initiatives and business objectives, ensuring the team's work aligns with company goals.

Is 40 too late for data science?

Age is not a barrier to becoming a data science manager; many professionals transition into data science roles later in their careers. Success depends on relevant skills, experience, and continuous learning in areas like programming, statistics, and machine learning. Employers value diverse backgrounds and practical expertise regardless of age.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often use this principle to focus on the most impactful features, models, or data subsets to improve efficiency and outcomes in projects.

What is the role of a data science manager?

A data science manager oversees data science teams, guiding project priorities, setting strategic goals, and ensuring the effective use of data analysis and modeling techniques. They coordinate between technical staff and business stakeholders, often requiring skills in leadership, communication, and familiarity with tools like Python, R, or SQL. Their responsibilities include managing workflows, mentoring team members, and ensuring project deliverables align with organizational objectives.

How much do data scientist managers make?

Data Science Managers typically earn between $110,000 and $160,000 annually, with salaries varying based on experience, location, and company size. They often oversee teams of data scientists, coordinate projects, and require strong skills in analytics tools and leadership. Senior roles or those in high-cost areas can offer higher compensation.

What are the key skills and qualifications needed to thrive in the Data Science Manager position, and why are they important?

To thrive as a Data Science Manager, you need strong analytical skills, experience in machine learning and data analytics, and a background in statistics or computer science, often supported by an advanced degree. Familiarity with tools like Python, R, SQL, cloud platforms, and experience managing data science projects are highly valued, and certifications such as Certified Analytics Professional (CAP) can be advantageous. Excellent leadership, project management, and communication skills are crucial for guiding teams and translating technical findings for stakeholders. These abilities ensure effective team performance, successful project delivery, and the alignment of data science initiatives with organizational goals.

What are the most commonly searched types of Data Science jobs in Minnesota? The most popular types of Data Science jobs in Minnesota are:
What are popular job titles related to Data Science Manager jobs in Minnesota? For Data Science Manager jobs in Minnesota, the most frequently searched job titles are:
What job categories do people searching Data Science Manager jobs in Minnesota look for? The top searched job categories for Data Science Manager jobs in Minnesota are:
What cities in Minnesota are hiring for Data Science Manager jobs? Cities in Minnesota with the most Data Science Manager job openings:
Infographic showing various Data Science Manager job openings in Minnesota as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $95,145 per year, or $45.7 per hour.
Principal Data Scientist

Principal Data Scientist

General Mills

Minneapolis, MN • On-site

Full-time

Medical, Retirement

Posted 22 days ago


General Mills rating

8.2

Company rating: 8.2 out of 10

Based on 110 frontline employees who took The Breakroom Quiz

60th of 401 rated food and drinks producers


Job description

OVERVIEW: 

The Principal Data Scientist position is a senior technical leader who strategizes enterprise-grade AI solutions, spanning agentic AI, NLP, optimization & machine learning, to unlock measurable value across the Supply Chain and aligned domains. By working as a strategic partner to Supply Chain and cross-functional leaders in Product and Engineering, this role translates complex business requirements into rigorously framed analytical problems and robust, production-grade decisioning systems.

The Principal Data Scientist shapes and governs the end-to-end AI architecture and strategic roadmap on a variety of AI platforms, ensuring AI capabilities are secure, scalable, and aligned with General Mills technology strategy. They elevate the broader Data Science community through technical mentorship and leadership in AI/ML best practices that accelerate high-quality solution delivery and responsible AI adoption.

KEY ACCOUNTABILITIES: 

  • Lead, design, and execute novel, end-to-end AI solutions and systems that help business partners achieve strategic objectives through advanced analytics, modeling, and optimization, with a primary focus on complex Supply Chain decisioning.
  • Partner with data science leadership, engineering, AI platform teams, and business stakeholders to define, prioritize, and deliver production-grade AI/ML products and services, leveraging best-in-class tools, frameworks, and cloud-native architectures on GCP.
  • Provide technical leadership through strong business partnership, challenging assumptions, offering alternate architectural patterns, and making informed trade-offs between complexity, performance, cost, and long-term maintainability.
  • Lead the reference architecture, design, and implementation of LLMs, NLP, and computer vision-driven solutions, owning patterns for problem framing, data curation, model lifecycle, and integration with core enterprise platforms and applications.
  • Provide technical oversight across core data science methodologies—including statistical, machine learning, and optimization approaches, ensuring method selection, validation, and implementation are rigorous, fit-for-purpose, and consistent with AI standards.
  • Partner closely with AI Leadership, ML Engineering, and business stakeholders to define and evolve the architecture for agentic AI and retrieval-augmented systems, establishing standards, guardrails, and reusable components.
  • Own the creation and operationalization of production-ready, scalable AI platforms, services, and models that provide real-time or near-real-time insights and decisions, fully aligned with General Mills technology standards for security, reliability, observability, and lifecycle management.
  • Provide technical leadership for analytical solution design and experimentation through hypothesis-driven approaches, robust evaluation strategies, and clear error taxonomies, with strong documentation and governance to ensure transparency, reproducibility, and reuse across capabilities.
  • Serve as a key member of the Data Science leadership team, shaping technical strategy, multi-year capability roadmaps, architectural standards, and operating practices that scale AI impact across the enterprise.
  • Coach and develop data scientists and adjacent talent through deep technical reviews and mentoring on advanced AI concepts, domain best practices, and effective use of shared platforms and patterns.
  • Champion Responsible AI by ensuring privacy, security, and governance compliance; proactively identifying and reducing model risks and embedding responsible AI principles into architecture, processes, and user experiences.
  • Act as an internal and external thought leader on AI strategy, architecture, and data science, representing the Digital and Technology organization in forums, communities of practice, and key stakeholder engagements.

MINIMUM QUALIFICATIONS:

  • 10+ years of experience in data science / applied analytics, with ownership of end-to-end solutions from problem framing through production and measurable business impact with at least 3 years in a Principal, Lead, or equivalent senior technical level. 
  • Advanced degree in a quantitative field (Data Science, Computer Science, Engineering, Statistics, Math, Operations Research, or related).
  • Strong expertise in core data science methodologies (statistical modeling, machine learning, optimization) and their practical application to complex business problems.
  • Hands-on experience architecting and deploying scalable AI/ML solutions on a major cloud platform (preferably GCP).
  • Proven track record of building and operating production-grade models and decisioning systems at scale, including monitoring, performance management, and lifecycle governance.
  • Demonstrated technical leadership setting technical direction, establishing standards, and influencing architecture and platform decisions.
  • Experience leading complex AI/ML programs across multiple teams, with strong grasp of project/program management fundamentals (roadmaps, prioritization, risk/dependency management).
  • Experience with unstructured data and advanced AI (e.g., LLMs, NLP, computer vision) integrated into business workflows and applications.
  • Strong communication skills, with the ability to clearly explain analytical concepts, results, and trade-offs to both technical and non-technical stakeholders.
  • Proficiency with modern data science engineering practices: version control, code review, testing, CI/CD for models, and agile delivery.
  • Demonstrated ability to mentor and develop other data scientists, leading by example on modeling rigor, experimentation, and documentation.
  • Proven ability to stay current on evolving AI/ML technologies and to anticipate, evaluate, and advocate for appropriate adoption within the enterprise.

PREFERRED QUALIFICATIONS: 

  • Deep experience applying data science and AI to Supply Chain domains (e.g., planning, logistics, manufacturing, sourcing).
  • Experience leading solutions that combine traditional modeling (predictive/prescriptive analytics, optimization) with newer paradigms (LLMs, agentic AI, RAG) in production.
  • Exposure to large-scale data processing and modern stack components
  • Evidence of thought leadership in data science (e.g., internal forums, publications, or open-source contributions).

ADDITIONAL CONSIDERATIONS: 

  • International relocation or international remote working arrangements (outside of the US) will not be considered.
  • Applicants for this position must be currently authorized to work in the United States on a full-time basis. General Mills will not sponsor applicants for this position for work visas.

Salary Range
The salary range for this position is $146900.00 - $245000.00 / Annually. At General Mills we strive for each employee's pay at any point in their career to reflect their experiences performance and skills for their current role. The salary range for this role represents the numerous factors considered in the hiring decisions including, but not limited to, educations, skills, work experience, certifications, etc. As such, pay for the successful candidate(s) could fall anywhere within the stated range. Beyond base salary, General Mills offers a competitive Total Rewards package focusing on your overall well-being. We are proud to offer a foundation of health benefits, retirement and financial wellbeing, time off programs, wellbeing support and perks. Benefits may vary by role, country, region, union status, and other employment status factors. You may also be eligible to participate in an annual incentive program. An incentive award, if any, depends on various factors, including, individual and organizational performance.

Reasonable Accommodation Request
If you need to request an accommodation during the application or hiring process, please fill out our online accommodations request form by following this link: Accommodations Request. Qualifications:UNAVAILABLEEducation:UNAVAILABLEEmployment Type: FULL_TIME


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About General Mills

Sourced by ZipRecruiter

General Mills, Inc. manufactures some of the most beloved foods in the world, including Cheerios and Lucky Charms, Nature Valley granola bars, Totino's pizza rolls, and Yoplait yogurt. Blue Buffalo became part of General Mills in 2018, so even your pets love us too.

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Minneapolis, MN, US

Year founded

1928