1

Natural Science Manager Jobs in Minnesota (NOW HIRING)

NR Supervisor

New Ulm, MN · On-site

$84K - $120K/yr

While not required, a bachelor's or advanced degree in natural resource management, parks & recreation, natural science, communications, public relations, business management, political science ...

Emphasizes observational skills and evidence-based reasoning, connecting earth science to natural disaster preparedness, environmental conservation, and resource management. * Curriculum Awareness ...

Emphasizes observational skills and evidence-based reasoning, connecting earth science to natural disaster preparedness, environmental conservation, and resource management. * Curriculum Awareness ...

Emphasizes observational skills and evidence-based reasoning, connecting earth science to natural disaster preparedness, environmental conservation, and resource management. * Curriculum Awareness ...

Bachelor's degree in environmental science, natural science, environmental engineering, or a ... Ability to manage multiple tasks, work independently, and adapt in afastpacedconsulting environment

Bachelor's degree in environmental science, natural science, environmental engineering, or a ... Ability to manage multiple tasks, work independently, and adapt in afastpacedconsulting environment

next page

Showing results 1-20

Natural Science Manager information

See Minnesota salary details

$28.4K

$102.4K

$115.6K

How much do natural science manager jobs pay per year?

As of Sep 14, 2026, the average yearly pay for natural science manager in Minnesota is $102,422.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,700.00 and $114,100.00 per year, depending on experience, location, and employer.

What is a natural science manager?

Natural Science Managers are professionals who oversee the work of scientists, including chemists, physicists, and biologists, in organizations such as research institutions, government agencies, or private companies. They are responsible for planning and coordinating scientific research and development projects, managing budgets, and ensuring that their teams meet project goals and comply with regulations. In addition to administrative duties, they may also help develop research strategies and interpret results. Natural Science Managers usually have extensive experience in a scientific discipline and strong leadership skills.

How do natural science managers balance administrative duties with leading scientific research projects?

Natural Science Managers often split their time between overseeing administrative tasks—such as budgeting, scheduling, and compliance—and guiding the scientific direction of their teams. This dual responsibility requires strong organizational skills, as managers must ensure that research projects stay on track while also managing staff, reporting progress, and securing funding. Effective Natural Science Managers create clear communication channels and delegate tasks appropriately to balance these demands, enabling them to support both the scientific and operational success of their departments.

What are the key skills and qualifications needed to thrive as a natural science manager?

To thrive as a Natural Science Manager, you need a strong background in scientific research, project management, and typically a graduate degree in a relevant science field. Familiarity with data analysis software, laboratory management systems, and sometimes specific certifications in project management or environmental regulations are commonly required. Leadership, effective communication, and problem-solving skills help managers coordinate teams and translate scientific findings into actionable strategies. These combined skills ensure successful project execution, regulatory compliance, and the advancement of organizational goals in scientific settings.

What is the difference between Natural Science Manager vs Environmental Scientist?

AspectNatural Science ManagerEnvironmental Scientist
Required CredentialsBachelor's or higher in natural sciences, often with management experienceBachelor's or higher in environmental science, biology, or related fields
Work EnvironmentLeads teams in research, labs, or field projects within organizationsConducts fieldwork, research, and data analysis in environmental settings
Employer & Industry UsageResearch institutions, government agencies, private companiesEnvironmental consulting firms, government agencies, NGOs
Common Search & Comparison IntentUnderstanding managerial roles in natural sciencesEnvironmental research and fieldwork roles

The main difference is that a Natural Science Manager oversees scientific teams and projects within natural sciences, focusing on management and coordination, while an Environmental Scientist primarily conducts research and fieldwork to assess environmental conditions. Both roles require relevant scientific credentials, but the manager's role emphasizes leadership and organizational skills.

How long does it take to become a natural science manager?

Becoming a natural science manager typically requires at least a bachelor's degree in a relevant field, which takes about four years, followed by several years of experience in scientific research or related roles. Many positions also prefer candidates with a master's or doctoral degree and leadership skills, which can extend the timeline to 8-10 years or more depending on career progression and industry requirements.

How much do natural science managers make?

Natural science managers in Colorado typically earn an average annual salary of around $100,000 to $130,000, depending on experience, education, and the specific industry. They often oversee research projects, manage teams, and require strong knowledge of scientific methods and project management skills.

What cities in Minnesota are hiring for Natural Science Manager jobs?

Cities in Minnesota with the most Natural Science Manager job openings:

Infographic showing various Natural Science Manager job openings in Minnesota as of August 2026, with employment types broken down into 85% Full Time, 12% Part Time, 2% Contract, and 1% Nights. Highlights an 81% Physical, 2% Hybrid, and 17% Remote job distribution, with an average salary of $102,422 per year, or $49.2 per hour.

Data Science Manager, Gen AI - SFL Scientific

Minneapolis, MN

Deloitte
Finance and Insurance • 10K+ employees

Full-time

Re-posted 27 days ago


Deloitte rating

8.2

Company rating: 8.2 out of 10

Based on 93 frontline employees who took The Breakroom Quiz


Job description

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific is a Deloitte Business that is part of our Strategy Offering, within our broader Strategy & Transactions practice mentioned above. This specialized team brings together several key capabilities to architect integrated programs that transform our clients' businesses. We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy, and other industries. Join us at SFL Scientific to expand your technical acumen through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.

Recruiting for this role ends on 10/31/2026.

Work You'll Do
As a Data Science Manager at SFL Scientific, you will develop and manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases. The Data Science Manager will provide leadership for our comprehensive data science and AI initiatives, developing and executing strategies that deliver measurable business and scientific outcomes. Successful candidates will be an expert in using state-of-the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications and use cases. Data Science Managers are also responsible for but not limited to: 

  • Support identification of high-value AI opportunities that drive industry advantage, representing an organization's AI vision through strategic delivery and industry.
  • Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
  • Engage and guide a diverse set of clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
  • Lead comprehensive AI initiatives spanning predictive and generative AI, overseeing development of advanced models and ensuring systems are scalable, efficient, and adhere to requirements and AI guidelines
  • Support an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for production and research applications
  • Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
  • Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
  • Mentor, motivate, and coach junior data scientists on technical best practices and inspire professional development
  • Develop key skillsets and delivery experience to grow into leadership or non-technical management and business roles

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.

Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. We are advancing both predictive and generative AI technologies while maintaining a commitment to data-driven decision making across all levels of a client's organization, building solutions that drive growth and create meaningful impact. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Qualifications

Required:

  • Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
  • 6+ years of experience working in data science, data engineering, software engineering, or MLOps
  • 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
  • 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
  • 6+ years of experience with traditional ML and deep learning techniques (CNNs, RNNs, LSTMs, GANs), model tuning, and validation of developed algorithms
  • 4+ years of experience managing teams and delivering complex and critical projects
  • Live within commuting distance to one of Deloitte's consulting offices
  • Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve
  • Limited immigration sponsorship may be available

Preferred:

  • Experience with cloud deployment (AWS, Azure, GCP), such as building and scaling in AWS SageMaker or Azure ML Studio
  • Experience with developing and testing GenAI solutions
  • Experience in a client-facing role or internal AI product development role
  • Highly proficient written and verbal skills to support briefings, proposals, technical sprint plans, solution reports, progress updates, and executive presentations

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $155,600 to $306,800.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Our Deloitte Strategy & Transactions team helps guide clients through their most critical moments and transformational initiatives. From strategy to execution, this team delivers integrated, end-to-end support and advisory services covering valuation modeling, cost optimization, restructuring, business design and transformation, infrastructure and real estate, mergers and acquisitions (M&A), and sustainability. Work alongside clients every step of the way, helping them navigate new challenges, avoid financial pitfalls, and provide practical solutions at every stage of their journey-before, during, and after any major transformational projects or transactions.
SFL Scientific is a Deloitte Business that is part of our Strategy Offering, within our broader Strategy & Transactions practice mentioned above. This specialized team brings together several key capabilities to architect integrated programs that transform our clients' businesses. We are hiring a Data Science Manager to support the technical design, development, and deployment of novel AI solutions across healthcare, life sciences, manufacturing, consumer, energy, and other industries. Join us at SFL Scientific to expand your technical acumen through the lens of professional services and consulting and help create novel solutions to advance your data science & AI career.

Recruiting for this role ends on 10/31/2026.

Work You'll Do
As a Data Science Manager at SFL Scientific, you will develop and manage a team of developers to deliver novel solutions in the AI and GenAI domains. You will be responsible for the technical direction of client engagements while defining the project strategy, communicating complex concepts to both technical and non-technical audiences, and leading solution development to solve our clients' use cases. The Data Science Manager will provide leadership for our comprehensive data science and AI initiatives, developing and executing strategies that deliver measurable business and scientific outcomes. Successful candidates will be an expert in using state-of-the-art technologies such as computer vision, natural language processing (NLP), time-series analysis, graph neural networks, and other AI/ML subdomains to solve complex business problems across diverse applications and use cases. Data Science Managers are also responsible for but not limited to: 

  • Support identification of high-value AI opportunities that drive industry advantage, representing an organization's AI vision through strategic delivery and industry.
  • Serve as the technical lead on projects to drive the technical strategy, roadmap, and prototyping of AI/ML solutions to meet each clients' unique requirements
  • Engage and guide a diverse set of clients with high autonomy in AI strategy and adoption, including understanding organizational needs, performing exploratory data analysis (EDA), building and validating models, and deploying models into production
  • Lead comprehensive AI initiatives spanning predictive and generative AI, overseeing development of advanced models and ensuring systems are scalable, efficient, and adhere to requirements and AI guidelines
  • Support an interdisciplinary team of data scientists, engineers, and solution architects to achieve technical delivery objectives and real-world performance for production and research applications
  • Lead in the research and adoption of industry best practices for validation and deployment of models; support best delivery practices, code review, UAT, unit, and integration tests
  • Present to key stakeholders, including solution findings and options for potential deployment infrastructure, hardware, software, cloud, etc.
  • Mentor, motivate, and coach junior data scientists on technical best practices and inspire professional development
  • Develop key skillsets and delivery experience to grow into leadership or non-technical management and business roles

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to mentor and provide clear guidance to others

The Team
Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.

Specifically, SFL Scientific, a Deloitte Business, is a data science professional services practice focused on strategy, technology, and solving business challenges with Artificial Intelligence (AI). The team has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. We are advancing both predictive and generative AI technologies while maintaining a commitment to data-driven decision making across all levels of a client's organization, building solutions that drive growth and create meaningful impact. Made up of experienced AI strategists, data scientists, and AI engineers, they serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses.

Qualifications

Required:

  • Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.)
  • 6+ years of experience working in data science, data engineering, software engineering, or MLOps
  • 6+ years of experience in AI/ML algorithm development workflow and data analysis in the major data modalities from NLP, time-series analysis, computer vision to graph models
  • 6+ years of experience in core programming languages and data science packages (Python, Keras, PyTorch, Pandas, Scikit-learn, Docker, Kubernetes, etc.)
  • 6+ years of experience with traditional ML and deep learning techniques (CNNs, R...

What Deloitte employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom