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Director Data Science Jobs in Rochester, MN (NOW HIRING)

Mayo Clinic

Director - AI Digital Pathology

Rochester, MN · Hybrid

$204K - $306K/yr

Directing a multidisciplinary team of AI/ML engineers, software developers, and research scientists ... Partner with clinical, operational, technical, legal, compliance, and data leaders to advance AI ...

Mayo Clinic

Senior Analytics Advisor-Hybrid

Rochester, MN · Hybrid

$107K - $150K/yr

... direct analytics projects through all analytics project stages: Business Understanding, Data ... Bachelor's Degree in Accounting, Finance, Business Administration, Data Science, or Computer ...

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Director Data Science information

See Rochester, MN salary details

$54.9K

$157.4K

$248K

How much do director data science jobs pay per year?

As of Aug 1, 2026, the average yearly pay for director data science in Rochester, MN is $157,428.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,800.00 and $192,600.00 per year, depending on experience, location, and employer.

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

To thrive as a Director Data Science, you need a deep understanding of advanced statistical modeling, machine learning, and data strategy, typically backed by an advanced degree in a quantitative field and significant leadership experience. Proficiency with tools such as Python, R, SQL, cloud data platforms, and familiarity with data governance frameworks and certifications like Certified Analytics Professional (CAP) are common requirements. Outstanding communication, stakeholder management, and team leadership abilities make candidates stand out in this position. These skills ensure the successful translation of complex data insights into actionable business strategies and the effective leadership of high-performing data science teams.

What does a data science director do?

A data science director oversees the data science team, develops strategic data initiatives, and ensures the effective use of data analytics to support business goals. They often manage projects, collaborate with other departments, and have expertise in statistical methods, machine learning, and data management tools. Strong leadership and communication skills are essential for guiding teams and translating complex data insights into actionable strategies.

Can data scientists make $300k?

Data scientists, especially those in senior or specialized roles at large companies or in high-cost-of-living areas, can earn $300,000 or more annually. Achieving this level often requires extensive experience, advanced skills in machine learning and programming, and sometimes leadership responsibilities or equity compensation.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as the Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this rule to prioritize variables, focus on impactful data, and optimize models efficiently.

What is a Director Data Science job?

A Director of Data Science leads a team of data scientists and analysts to drive data-driven decision-making within an organization. They develop strategic initiatives, oversee machine learning and analytics projects, and collaborate with executives to align data efforts with business goals. The role requires expertise in data science, leadership, and communication to translate complex insights into actionable strategies.

What is the highest paid job in data science?

The highest paid roles in data science are typically senior positions such as Chief Data Officer or Director of Data Science, with salaries often exceeding $200,000 annually. These roles require extensive experience, advanced skills in machine learning, and leadership capabilities, often complemented by advanced degrees and certifications.

What types of teams and professionals will I collaborate with as a Director Data Science?

As a Director Data Science, you will regularly collaborate with cross-functional teams including business analysts, data engineers, software developers, product managers, and senior executives. Your role often involves translating business goals into data-driven strategies, as well as mentoring and guiding data scientists and analysts on your team. You may also work closely with stakeholders from marketing, operations, and finance to align analytics initiatives with organizational objectives. This collaborative environment fosters innovative solutions and ensures data science efforts have a meaningful impact on overall business performance.

What are the most commonly searched types of Data Science jobs in Rochester, MN? The most popular types of Data Science jobs in Rochester, MN are:
What cities near Rochester, MN are hiring for Director Data Science jobs? Cities near Rochester, MN with the most Director Data Science job openings:
Director Data Science jobs near you

Principal Data & Analytics Strategist

Mayo Clinic

Rochester, MN

Other

Medical, Dental, Vision, Retirement

Posted 2 days ago

New

Mayo Clinic rating

7.8

Company rating: 7.8 out of 10

Based on 692 frontline employees who took The Breakroom Quiz

105th of 887 rated healthcare providers

Job description

Why Mayo Clinic

Mayo Clinic is top-ranked in more specialties than any other care provider according to U.S. News & World Report. As we work together to put the needs of the patient first, we are also dedicated to our employees, investing in competitive compensation and comprehensive benefit plans - to take care of you and your family, now and in the future. And with continuing education and advancement opportunities at every turn, you can build a long, successful career with Mayo Clinic.

Benefits Highlights
  • Medical: Multiple plan options.
  • Dental: Delta Dental or reimbursement account for flexible coverage.
  • Vision: Affordable plan with national network.
  • Pre-Tax Savings: HSA and FSAs for eligible expenses.
  • Retirement: Competitive retirement package to secure your future.

Responsibilities

The Principal Data Analytics & AI Strategist is a principallevel individual contributor who serves as a technical authority and enterpriselevel thought leader for data, analytics, and AI solution direction across products, platforms, and strategic problem areas. This role shapes how enterprise data, analytics and AI strategy is translated into scalable solution patterns, architectural guardrails, and delivery models that can be consistently executed across teams. 

The role connects system-level technical decisions to broader enterprise data and analytics strategy, governance, and investment intent-ensuring initiatives are interoperable, governable, and positioned to deliver sustained, measurable value at scale. The Principal Data Analytics & AI Strategist operates across high ambiguity, making and documenting complex tradeoffs related to platform capabilities, data architecture, analytics and AI patterns, operating constraints, and sequencing of delivery.

Working across domains and portfolios, the Principal Data Analytics & AI Strategist influences the full solution lifecycle-from opportunity framing and options analysis through solution design guidance and delivery oversight. The role defines and socializes reference architectures, preferred patterns, and decision frameworks, supports highrisk or highimpact initiatives, and accelerates progress through handson exploration and prototyping where early technical validation is critical.

 The Principal Data Analytics & AI Strategist partners closely with senior leaders and practitioners across data engineering, analytics/BI, AI/ML, platform, security, and governance functions to align on technical direction, surface risks and dependencies early, and enable timely, enterprisewide decisionmaking-exerting influence without direct authority to drive clarity, consistency, and execution momentum.


Qualifications
  • Bachelor's degree in computer science, information systems, engineering, mathematics, statistics, data science, or related field from an accredited University or College is required.
  • Master's degree or PhD in a related field (e.g., computer science, data science, business analytics, healthcare informatics, or MBA) is preferred.
  • Extensive (15-20+ years) experience in enterprise data, analytics, and/or AI strategy, architecture, consulting, product/program delivery, or related discipline.
  • Demonstrated experience defining enterprise-level strategy and translating it into executable roadmaps, capability models, and delivery guardrails across multiple portfolios.
  • Proven ability to communicate complex technical implementation concepts to executive leadership, including architecture tradeoffs, investment options, risk, and sequencing; produces clear, decision-ready materials.
  • Strong working knowledge of modern data and analytics concepts (data products, data platforms, pipelines, BI/visualization, governance, metadata, quality, privacy/security fundamentals, and observability).
  • Experience influencing across senior stakeholders and cross-functional teams (engineering, analytics, AI/ML, security, privacy, architecture, governance) to drive alignment and decisions in ambiguous environments.
  • Experience operating in regulated environments (e.g., healthcare, research, financial services), with familiarity with privacy, compliance, governance, and responsible AI expectations.
  • Demonstrated facilitation skills for executive and technical audiences (workshops, strategic reviews, governance forums) and strong written communication skills.
  • Certification in one or more major cloud platforms (Google, Azure, etc)
  • Experience establishing or evolving enterprise data operating models (e.g., data product operating model, platform governance, domain engagement, stewardship models) and measuring adoption/maturity over time.
  • Experience developing and/or governing enterprise AI strategy, including responsible AI controls, model risk management, and GenAI/agentic patterns (grounding, evaluation, monitoring).
  • Experience with cloud data platforms and modern architecture patterns (lakehouse/warehouse, streaming/eventing, semantic layers/metrics, MDM/reference data), including cost/value tradeoffs.
  • Demonstrated experience building reusable playbooks, reference architectures, templates, and standards that scale delivery across multiple teams.

The ideal candidate will have prior experience in working through large scale AI transformations for organizations including creation of vector stores, Knowledge graphs, MCP servers and getting an organization data teams AI ready. 


Exemption Status
Exempt
Compensation Detail
$204,256.00 - $306,384.00 / year. Education, experience and tenure may be considered along with internal equity when job offers are extended.
Benefits Eligible
Yes
Schedule
Full Time
Hours/Pay Period
80
Schedule Details
M-F daytime hours 100% remote role, the employee needs to live within the US.
Weekend Schedule
As business needs dictate
International Assignment
No
Site Description
Just as our reputation has spread beyond our Minnesota roots, so have our locations. Today, our employees are located at our three major campuses in Phoenix/Scottsdale, Arizona, Jacksonville, Florida, Rochester, Minnesota, and at Mayo Clinic Health System campuses throughout Midwestern communities, and at our international locations. Each Mayo Clinic location is a special place where our employees thrive in both their work and personal lives. Learn more about what each unique Mayo Clinic campus has to offer, and where your best fit is. 

Equal Opportunity

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, gender identity, sexual orientation, national origin, protected veteran status or disability status. Learn more about the 'EOE is the Law'.  Mayo Clinic participates in E-Verify and may provide the Social Security Administration and, if necessary, the Department of Homeland Security with information from each new employee's Form I-9 to confirm work authorization.

Recruiter
Laura PercivalQualifications:
  • Bachelor's degree in computer science, information systems, engineering, mathematics, statistics, data science, or related field from an accredited University or College is required.
  • Master's degree or PhD in a related field (e.g., computer science, data science, business analytics, healthcare informatics, or MBA) is preferred.
  • Extensive (15-20+ years) experience in enterprise data, analytics, and/or AI strategy, architecture, consulting, product/program delivery, or related discipline.
  • Demonstrated experience defining enterprise-level strategy and translating it into executable roadmaps, capability models, and delivery guardrails across multiple portfolios.
  • Proven ability to communicate complex technical implementation concepts to executive leadership, including architecture tradeoffs, investment options, risk, and sequencing; produces clear, decision-ready materials.
  • Strong working knowledge of modern data and analytics concepts (data products, data platforms, pipelines, BI/visualization, governance, metadata, quality, privacy/security fundamentals, and observability).
  • Experience influencing across senior stakeholders and cross-functional teams (engineering, analytics, AI/ML, security, privacy, architecture, governance) to drive alignment and decisions in ambiguous environments.
  • Experience operating in regulated environments (e.g., healthcare, research, financial services), with familiarity with privacy, compliance, governance, and responsible AI expectations.
  • Demonstrated facilitation skills for executive and technical audiences (workshops, strategic reviews, governance forums) and strong written communication skills.
  • Certification in one or more major cloud platforms (Google, Azure, etc)
  • Experience establishing or evolving enterprise data operating models (e.g., data product operating model, platform governance, domain engagement, stewardship models) and measuring adoption/maturity over time.
  • Experience developing and/or governing enterprise AI strategy, including responsible AI controls, model risk management, and GenAI/agentic patterns (grounding, evaluation, monitoring).
  • Experience with cloud data platforms and modern architecture patterns (lakehouse/warehouse, streaming/eventing, semantic layers/metrics, MDM/reference data), including cost/value tradeoffs.
  • Demonstrated experience building reusable playbooks, reference architectures, templates, and standards that scale delivery across multiple teams.

The ideal candidate will have prior experience in working through large scale AI transformations for organizations including creation of vector stores, Knowledge graphs, MCP servers and getting an organization data teams AI ready. 

What Mayo Clinic employees say

Pay

Benefits

Hours and flexibility

Workplace

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About Mayo Clinic

Sourced by ZipRecruiter

Mayo Clinic is the largest integrated, not-for-profit medical group practice in the world. We're building the future, one where the best possible care is available to everyone — and more people can heal at home. Our relentless research turns into earlier diagnoses and new cures. That's how we inspire hope in those who need it most. At Mayo Clinic, experts work together to solve the most challenging unmet needs of patients. Our history of innovation dates back almost 150 years, when brothers Will and Charlie Mayo pioneered an integrated, team-based approach to medicine. Today, that trailblazing spirit drives innovations like Mayo Clinic Platform — which powers new technologies to change how care is delivered to all.

Industry

Hospitals

Company size

10,000+ Employees

Headquarters location

Rochester, MN, US

Year founded

1919

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