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Mayo Foundation for Medical Education and Research

Senior Data Informatics Business Partner

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What they do

A Clinical Data Analyst is responsible for gathering, compiling, modeling, validating, and analyzing clinical trial results data needed by pharmaceutical companies, governmental agencies, and biotechnology firms evaluate the effectiveness of their trial drugs. May be responsible for designing, testing, and implementing clinical data reporting systems for the clinical staff to use.

$90,984 / year median in Minnesota

-12% projected decline

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Job Description

The Senior Data Informatics Business Partner operates at the intersection of clinical practice, business operations, and enterprise data and analytics capabilities. This role provides essential informatics context and translation, ensuring that data, analytics, AI, and integration efforts are grounded in how information is created, interpreted, and acted on in real‑world settings. By understanding clinical and operational workflows, system touchpoints, and data movement across environments, the role helps align enterprise solutions with decision‑making needs. Serving as a key engagement point across multiple complex or interdependent domains, the Senior Data Informatics Business Partner builds trusted relationships with physicians, researchers, and operational leaders. The role reframes needs and questions into structured, outcome-oriented requests by guiding intent, scope, assumptions, and success criteria. The position plays a critical role in translating enterprise expectations around data governance, quality, privacy, responsible AI, and control requirements, helping teams understand how these considerations influence what is appropriate, feasible, and trustworthy in specific use cases. This senior role will develop and maintain intake mechanisms, including taxonomy and documentation that reflect outcomes, success criteria, assumptions, and adoption needs. The position guides outcome definition, assessment of feedback, and evaluation of impact across clinical and business domains.
Core job duties include:
Provide clinical and operational informatics context for data access, integration, and interoperability needs (e.g., workflows, system touchpoints, interoperability partners), beyond purely technical specifications. Analyze and interpret clinical and operational workflows to understand how data is generated, transformed, and used across systems, providing context that ensures data, analytics, and integration efforts align with real‑world decision‑making and practice. Serve as a senior engagement and advisory point for complex clinical or business domains, navigating competing priorities and guiding stakeholders toward shared, outcome‑focused requests. Advise stakeholders and delivery teams on the application of enterprise data governance, quality standards, privacy, and responsible AI requirements across complex use cases, identifying areas where policy interpretation or guidance refinement may be needed. Shape and document intake artifacts that clarify problem statements, intended outcomes, success measures, assumptions, constraints, and adoption considerations, ensuring requests are actionable and ready for delivery. Act as a liaison between business domains and Enterprise Data and Analytics delivery, governance, and enablement teams to maintain shared understanding throughout the intake and handoff process. Guide outcome definition and evaluation approaches for complex data and analytics initiatives, helping ensure impact, trust, and adoption can be assessed consistently across domains. Ensure adoption and trust considerations (who will use outputs, how they will be interpreted, and what support is needed) are explicitly attached to intake and translation efforts. Identify and synthesize recurring intake patterns, ambiguities, or friction and provide recommendations that inform refinement of intake processes, standards, or governance guidance. This vacancy is not eligible for sponsorship/ we will not sponsor or transfer visas for this position. Also, Mayo Clinic
DOES NOT
participate in the
F-1 STEM OPT
extension program. Bachelor's degree in healthcare, clinical informatics, informatics, business, public health, information systems, or a related field. A minimum of 8 years' relevant work experience and 3+ years working closely with clinical, research, operational, financial, or administrative stakeholders in a consultative or partnership‑oriented role. Experience working with or alongside data, analytics, AI, governance, or digital delivery teams in a healthcare or other regulated environment. Demonstrated ability to apply clinical or business informatics principles to translate domain needs into structured, outcome‑oriented data, analytics, or digital requests beyond traditional requirements gathering. Experience working in environments with multiple data‑producing systems, including understanding of how data is created, moved, and used across workflows and applications to support reporting, analytics, or operations. Advanced knowledge of enterprise data governance, data quality, master data, metadata management, privacy, and responsible AI concepts, and the ability to advise how policies and standards apply in real‑world contexts. Strong communication and facilitation skills, including the ability to listen, synthesize complex information, clarify ambiguity, tailor messaging to diverse audiences, and guide stakeholders toward actionable outcomes. Demonstrated experience operating independently in ambiguous, high‑impact environments, advising stakeholders on trade‑offs, feasibility, and appropriateness of data and analytics solutions. Background in clinical informatics, informatics engagement, business informatics, or intake/translation roles supporting data, analytics, or digital initiatives. Experience influencing or shaping intake, translation, or governance‑activation practices beyond individual requests, contributing to improved consistency or quality at a program or portfolio level. Experience working across complex system landscapes with end‑to‑end data movement, including understanding where data originates, how it flows through pipelines and systems, and how it is ultimately interpreted and acted on by users. Experience designing or contributing to measurement and evaluation frameworks that assess whether data, analytics, or AI solutions are achieving intended outcomes.