Principal Data & Analytics Strategist

Mayo Clinic•Rochester, MN

1d•$204,256 - $306,384

About The Position

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.

Requirements

Principal-level individual contributor
Technical authority and enterprise-level thought leader for data, analytics, and AI solution direction
Ability to shape enterprise data, analytics and AI strategy into scalable solution patterns, architectural guardrails, and delivery models
Ability to connect system-level technical decisions to broader enterprise data and analytics strategy, governance, and investment intent
Ability to operate across high ambiguity, making and documenting complex tradeoffs
Ability to influence the full solution lifecycle
Ability to define and socialize reference architectures, preferred patterns, and decision frameworks
Ability to support high‑risk or high‑impact initiatives
Ability to accelerate progress through hands‑on exploration and prototyping
Ability to partner closely with senior leaders and practitioners across data engineering, analytics/BI, AI/ML, platform, security, and governance functions
Ability to exert influence without direct authority

Responsibilities

Serves as a technical authority and enterprise-level thought leader for data, analytics, and AI solution direction across products, platforms, and strategic problem areas.
Shapes how enterprise data, analytics and AI strategy is translated into scalable solution patterns, architectural guardrails, and delivery models.
Connects system-level technical decisions to broader enterprise data and analytics strategy, governance, and investment intent.
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.
Influences the full solution lifecycle—from opportunity framing and options analysis through solution design guidance and delivery oversight.
Defines and socializes reference architectures, preferred patterns, and decision frameworks.
Supports high‑risk or high‑impact initiatives.
Accelerates progress through hands‑on exploration and prototyping where early technical validation is critical.
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.