The Principal Data Analytics & AI Strategist is a principal‑level individual contributor who serves as a technical authority and enterprise‑level 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 high‑risk or high‑impact initiatives, and accelerates progress through hands‑on 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, enterprise‑wide decision‑making—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.
About UsMayo 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.
- 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.
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.
Skills Required
- Bachelor's degree in computer science, information systems, engineering, mathematics, statistics, data science, or related field
- Master's degree or PhD in related field (e.g., computer science, data science, business analytics, healthcare informatics, or MBA)
- 15-20+ years experience in enterprise data, analytics, and/or AI strategy, architecture, consulting, product/program delivery, or related discipline
- 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 and produce 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, observability)
- Experience influencing senior stakeholders and cross-functional teams (engineering, analytics, AI/ML, security, privacy, architecture, governance)
- Experience operating in regulated environments (healthcare, research, financial services) with familiarity in privacy, compliance, governance, and responsible AI expectations
- Demonstrated facilitation skills for executive and technical audiences and strong written communication skills
- Certification in one or more major cloud platforms (e.g., Google, Azure)
- Experience establishing or evolving enterprise data operating models and measuring adoption/maturity
- Experience developing and/or governing enterprise AI strategy, including responsible AI controls, model risk management, and GenAI/agentic patterns
- Experience with cloud data platforms and modern architecture patterns (lakehouse/warehouse, streaming/eventing, semantic layers/metrics, MDM/reference data)
- Demonstrated experience building reusable playbooks, reference architectures, templates, and standards that scale delivery across multiple teams
- Prior experience with large-scale AI transformations including vector stores, knowledge graphs, and MCP servers (ideal)
Mayo Clinic Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Mayo Clinic and has not been reviewed or approved by Mayo Clinic.
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Retirement Support — A no-cost pension plus an employer-matched 403(b)/401(k) is positioned as a standout differentiator, offering strong long-term financial security. Feedback suggests this retirement combination elevates overall total rewards even when base pay is moderate.
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Healthcare Strength — Expanded medical networks, enhanced fertility coverage, and employer absorption of a plan year’s premium increases point to robust healthcare offerings. Feedback suggests annual updates maintain breadth and competitiveness of coverage.
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Parental & Family Support — Adoption assistance, dependent scholarships, child and elder-care resources, and EAP services provide meaningful family-oriented support. Feedback suggests these programs add tangible value beyond salary alone.
Mayo Clinic Insights
What We Do
Mayo Clinic is the first and largest integrated, not-for-profit medical group practice in the world. Doctors from every medical specialty work together to care for patients, joined by common systems and a philosophy of "the needs of the patient come first." More than 3,800 physicians and scientists and 50,900 allied health staff work at Mayo Clinic, which has sites in Rochester, Minn., Jacksonville, Fla., and Scottsdale/Phoenix, Ariz. Mayo Clinic also serves over 70 communities through Mayo Clinic Health System with locations in MN, IA, and WI. Collectively, these locations care for more than 1 million people each year.
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