Data Innovation Partner Senior

About the Role

The Data Innovation Partner Senior is a senior individual contributor who delivers significant, enterprise-visible work within the Data Innovation Partner function. This role advances analytics capabilities through emerging technology and innovation while scaling enterprise adoption, footprint, and value realization. The position actively contributes to the enterprise's AI journey, applying responsible AI, machine learning, and emerging analytics practices to initiatives that enhance patient care, operations, and strategic decision-making.

The Senior Partner independently owns meaningful initiatives from intake through delivery, applying established methodologies, frameworks, and standards. They translate strategy into execution by designing solutions, running experiments, driving adoption, measuring outcomes, and sharing lessons learned. The role also involves mentoring less experienced Partners, contributing to team methodology, and partnering with senior stakeholders to translate business problems into analytical solutions. Data integrity is embedded into all work, in collaboration with the Data Integrity team.

Responsibilities

• Delivery & Execution
  • Independently own significant initiatives from intake through delivery, applying team methodologies, frameworks, and standards.
  • Design and deliver innovation experiments and adoption activities with measurable outcomes (e.g., learning, ROI, utilization, value realized).
  • Contribute to AI, machine learning, and emerging technology initiatives, adhering to enterprise standards for responsible AI, evaluation criteria, and integration patterns.
  • Participate in team forums (standups, planning, retrospectives) and contribute to continuous improvement of practices.
  • Anticipate and proactively raise risks or blockers within initiatives to Leads/Principals for coordination.
  • Standardize workflows and reduce cycle time by identifying and sharing repeatable patterns from delivery work.
• Integration & Alignment
  • Partner with stakeholders to translate business needs into innovation experiments and adoption plans aligned with enterprise strategy and governance.
  • Coordinate with peer Senior Partners to share methodology, avoid duplication, and align on approaches.
  • Apply analytical frameworks and evaluation standards, including AI/ML considerations for scale, risk, generative AI use cases, and analytics adoption for ROI and user enablement.
  • Apply responsible AI standards (e.g., data privacy, model transparency, bias awareness, HIPAA/CMS alignment, human oversight) to AI/ML work.
  • Contribute to enterprise programs and initiatives, providing practitioner input on approach and methodology.
  • Identify integrity, risk, or readiness considerations and escalate to Lead/Principal or Data Integrity partners as needed.
• Specialty Depth & Continuous Improvement
  • Build and maintain recognized depth in a specialty area (e.g., innovation, analytics adoption) and serve as the trusted go-to for the peer group.
  • Contribute to team methodology, playbooks, and standards by sharing best practices and refining approaches based on delivery experience.
  • Apply value measurement approaches to evaluate initiatives and contribute lessons learned to inform framework refinement.
  • Stay current with AI, machine learning, and emerging analytics developments relevant to the specialty area.
  • Embed data quality, lineage, and integrity considerations into initiatives, partnering with the Data Integrity team on standards.
• Influence & Stewardship
  • Mentor less experienced Partners through coaching, pairing, work review, and knowledge sharing.
  • Represent initiatives and specialty in cross-functional planning, working sessions, and stakeholder forums.
  • Partner with peer Seniors to align on practitioner-level coordination and share lessons across teams.
  • Model a collaborative, evidence-driven culture that reflects enterprise values and contributes to psychological safety.
  • Support Lead and Principal Partners in preparing communications and materials for executive and governance forums.
  • Contribute to enterprise data literacy and AI literacy by translating specialty depth into accessible guidance.
  • Champion continuous improvement by questioning assumptions, running retrospectives, and applying learnings.

Requirements

• Education & Experience
  • Bachelor’s Degree in Business/Innovation, Data Science, Computer Science, Engineering, Health Administration, Organizational Development, Adult Learning, Communications, or a related field — or equivalent years of experience.
  • 7+ years in analytics, coding development, analytics enablement/adoption, or organizational change tied to data and technology.
  • 5+ years in each of the following:
    • Applying ROI analysis, performance indicators, and impact metrics to evaluate program or initiative outcomes.
    • Analytics, business intelligence, digital transformation, or analytics adoption/change enablement with demonstrated impact beyond a single project or team.
    • Supporting performance improvement, process optimization, business transformation, or project/change management initiatives.
  • 3+ years in each of the following:
    • Using business intelligence tools (e.g., Power BI, Tableau, Epic SlicerDicer) to enable analytics adoption, decision-making, and user education.
    • Using portfolio and work management tools (e.g., ServiceNow, Azure DevOps, Jira) for intake, routing, documentation, prioritization, and tracking.
    • Developing adoption and enablement metrics (e.g., usage telemetry, training impact, satisfaction) to measure analytics ROI.
    • Serving as a recognized subject matter contributor in innovation, analytics adoption, or a related specialty.
  • 2+ years in each of the following:
    • Owning significant initiatives end-to-end with quantified outcomes (e.g., delivery milestones, adoption/utilization, measurable value).
    • Working with data quality, lineage, metadata, or data governance concepts in partnership with integrity/governance functions.
    • Mentoring or supporting less experienced practitioners through coaching, pairing, or work review.
    • At least one AI, machine learning, or emerging technology initiative (preferred).
• Certifications
  • Epic Cogito Fundamentals (COG170) certification.
  • Epic Cogito Project Manager (COG300) certification.
  • LEAN certification.
  • Completion of Epic SQL I and SQL II coursework.
  • Completion of advanced role-aligned learning paths in technology and people leadership (e.g., DataCamp tracks, Epic fundamentals, change management micro-credentials), with at least 50 hours annually within 1 year.
  • Innovation Track: Agile Scrum Master certification within 1 year (preferred).
  • Advisory & Adoption Track: APMG Change Management Foundation or equivalent recognized change-adoption credential within 1 year (preferred).

Preferred Qualifications

• Master’s Degree in Business Administration, Health Administration, Data Analytics, Organizational Development, or a related field.
• 0–2 years SQL experience in a relational database or equivalent combination of education and experience.
• Proficiency in SQL, Python or R, and cloud data platforms (e.g., Azure Data Lake, Databricks, Synapse, Snowflake) with ability to design data models, transformations, and integrations at scale.
• Foundational credential or coursework in AI, machine learning, or responsible AI practices (e.g., Microsoft AI Fundamentals, Google AI Essentials, Databricks fundamentals, healthcare AI ethics).
• 2+ years applying AI, machine learning, or generative AI capabilities to analytics initiatives (e.g., designing prompts, integrating AI-assisted analysis, evaluating model outputs).
• 3+ years working with healthcare data ecosystems (clinical, operational, financial, regulatory) with demonstrated understanding of Epic, Caboodle, or comparable platforms, and awareness of HIPAA, CMS, and clinical data implications.
• Advanced technical credential aligned to team assignment or specialty (e.g., Azure AI Engineer, Databricks ML Professional, Tableau/Power BI advanced certifications).
• Healthcare environment experience.
• Foundational understanding of data observability, metadata management, and lineage practices.
• Familiarity with Epic analytics ecosystems (Cogito, Caboodle, Radar).
• Demonstrated impact beyond a single team (e.g., contributing to enterprise standards, adoption playbooks, or maturing communities of practice).
• Experience participating in governance councils, technical review boards, or portfolio prioritization forums.
• Formal change-management or product ownership training (e.g., CCMP, APMG, PROSCI, CSPO/CPO).
• 3+ years partnering with senior stakeholders and executive-adjacent audiences (e.g., VPs, Directors, Physician Leaders) to translate business problems into analytical solutions and influence decision-making.

Schedule

Full time