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Data Science Manager Jobs in Minnesota (NOW HIRING)

Tactile Medical

Data Scientist

Minneapolis, MN

... Manage assigned projects to completion on time, within scope, and within budget. Other duties as assigned. Qualifications Required: Bachelor's degree in data science, statistics, mathematics ...

General Mills

Senior Data Scientist

Minneapolis, MN · On-site

$108K - $181K/yr

... 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 ...

General Mills

Senior Data Scientist

Minneapolis, MN · On-site +1

$108K - $181K/yr

... 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 ...

Tactile Medical

Data Scientist

Minneapolis, MN · On-site

$100K - $150K/yr

... • Manage assigned projects to completion on time, within scope, and within budget. • Other duties as assigned. Qualifications Required: • Bachelor's degree in data science, statistics ...

Resourcex,Inc.

Data Science Training

Saint Paul, MN

... IT staffing, IT talent management and IT services to the clients with unmatched quality ... We are offering online training on Data Science. . Provide OPT Stem Ext.: Guidance and support for ...

General Mills

Principal Data Scientist

Minneapolis, MN · On-site

Required : • 10+ years of experience in data science / applied analytics, with ownership of end ... management, and lifecycle governance. • Demonstrated technical leadership setting technical ...

General Mills

Sr. Data Scientist

Minneapolis, MN · On-site

$110K - $184K/yr

Identify and develop long-term data science processes, frameworks, tools, and standards. * Be a ... Experience developing and deploying Python packages and managing large-scale projects * Experience ...

General Mills

Sr. Data Scientist

Minneapolis, MN · On-site

$110K - $184K/yr

Identify and develop long-term data science processes, frameworks, tools, and standards. * Be a ... Experience developing and deploying Python packages and managing large-scale projects * Experience ...

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Data Science Manager information

See Minnesota salary details

$30.4K

$95.1K

$168.5K

How much do data science manager jobs pay per year?

As of Jul 24, 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:
Data Science Manager jobs near you
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.
Data Scientist

Data Scientist

Tactile Medical

Minneapolis, MN

Other

Posted 9 days ago

Tactile Medical rating

7.9

Company rating: 7.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

Job description

Position Summary
The Marketing Data Scientist is the predictive intelligence engine of TCMD's Marketing and Market Access organization. The primary work is finding connections in TCMD's data that no one has looked for yet, building predictive models, and translating validated models into forward-looking tools. This individual synthesizes insights from Tactile's internal and external data platforms to develop and explore hypotheses for growth. The role's mission is to surface predictive insights from these systems that inform commercial strategy before decisions are finalized. This role collaborates closely with marketing and market access leadership along with sales excellence and commercial leadership.

Accountabilities & Responsibilities
Exploratory analysis, hypothesis generation, feature engineering, model construction, and validation
Build and validate predictive models using appropriate machine learning and statistical methodologies
Translating validated models into forward-looking dashboards or automated scoring systems that are consumed with ease by stakeholders
Partner across the marketing organization to develop campaign lift attribution; building causal inference models isolating incremental referral lift from specific marketing programs
Develop predictive analytics supporting payer targeting and coverage expansion opportunities
Train commercial team users on how to interpret and act on model outputs and the specific decisions the model is designed to support
Communicate within marketing and market access on status of model pipeline and backlog; routinely collect voice of internal stakeholder needs to drive continuous improvement in data driven decision making
Manage assigned projects to completion on time, within scope, and within budget.
Other duties as assigned.

Qualifications

Required:
Bachelor's degree in data science, statistics, mathematics, computer science, economics, or a quantitative field with strong statistical foundations
4-7 years applied data science or machine learning experience, applied in commercial or operational environments
Experience creating predictive models for non-data-scientists to make real commercial or operational decisions
Comfort with messy healthcare commercial data, intellectual curiosity, and the communication discipline to translate technical findings into commercial language
Expert-level modern data science skills in Python and SQL working with structured data and machine-learning frameworks; version-controlled code development and deployment
Ability to transform messy, real-world healthcare data with missing values, inconsistent coding, and multiple granularities into reliable predictive model inputs
Working knowledge of Salesforce CRM architecture, healthcare claims data, Power BI/Fabric deployment environments

Preferred:
Master's or PhD in quantitative field
Understanding of referral-based commercial models, payer coverage dynamics, prior authorization processes, and DME/medical device reimbursement
Survival analysis experience - has applied time-to-event modeling in a commercial context (e.g., customer churn, time-to-conversion, time-to-renewal). Particularly relevant for funnel stage duration modeling and HCP churn prediction
Salesforce data architecture familiarity - understands the Salesforce object model well enough to write efficient queries and build reliable features from CRM data without requiring a Salesforce administrator to extract data
Power BI or Tableau development experience sufficient to deploy model scoring outputs as operational dashboards
Experience in a B2B2C or referral-based commercial model where the customer and the end user are different

What Tactile Medical employees say

Pay

Hours and flexibility

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