Data Innovation Partner Senior

About this role

Position Title

Data Innovation Partner Senior

Broadmoor Campus

Position Summary / Career Interest: The Data Innovation Partner Senior is a senior individual contributor who delivers significant, enterprise-visible work within the Data Innovation Partner function — advancing what analytics can do through emerging technology and innovation, and scaling how the enterprise uses analytics through strategic growth in adoption, footprint, and value realization. Together, these accountabilities position data as a foundation for every meaningful decision. This role actively contributes to the enterprise's AI journey, applying responsible AI, machine learning, and emerging analytics practices in initiatives that expand what data can do for patient care, operations, and strategic decision-making.

The Senior Partner independently owns meaningful initiatives from intake through delivery, applying established methodologies, frameworks, and standards set by Lead and Principal Partners. They translate strategy into execution — designing solutions, running experiments and driving adoption activities, measuring outcomes, and sharing lessons learned. As an experienced practitioner, the Senior contributes to team methodology, mentors less experienced Partners, and helps their peer group deliver consistently. The Senior partners with senior stakeholders and executive-adjacent audiences to translate business problems into analytical solutions. The Senior also embeds data integrity considerations into their work, partnering with the Data Integrity team to uphold enterprise standards. Success in this role is measured by initiative outcomes, quality of work, and growth of the practitioners around them.

Responsibilities and Essential Job Functions • **Delivery & Execution

• Independently own significant initiatives from intake through delivery within the team's scope, applying methodologies, frameworks, and standards set by senior peers.

• Design and deliver innovation experiments and adoption activities that produce measurable outcomes (learning, ROI, utilization, value realized).

• Contribute to the design and delivery of AI, machine learning, and emerging technology initiatives — applying enterprise standards for responsible AI, evaluation criteria, and integration patterns established by Principal Partners.

• Participate actively in team forums (standups, planning, retrospectives); contribute to continuous improvement of team practices.

• Anticipate risks and blockers within initiatives and raise them proactively to Leads/Principals for coordination.

• Contribute to standardizing workflows and reducing cycle time by identifying and sharing repeatable patterns from delivery work.

• **Integration & Alignment

• Partner with stakeholders across the organization to translate business needs into innovation experiments and adoption plans, aligned with enterprise strategy and governance standards.

• Coordinate with peer Senior Partners across the function to share methodology, avoid duplication, and align on approach.

• Apply analytical frameworks and evaluation standards to initiatives, inclusive of AI/ML considerations for scale and risk, generative AI use cases and guardrails, and analytics adoption considerations for ROI, user enablement, and value realization.

• Apply responsible AI standards — including data privacy, model transparency, bias awareness, HIPAA/CMS alignment, and human oversight expectations — to AI/ML work.

• Contribute to enterprise programs and initiatives; provide input on approach and methodology from a practitioner perspective.

• Identify integrity, risk, or readiness considerations within work and escalate to Lead/Principal or Data Integrity partners where needed.

• **Specialty Depth & Continuous Improvement

• Build and maintain recognized depth on a specialty area within innovation, analytics adoption, or a related domain; serve as the trusted go-to for the peer group on that specialty.

• Contribute to team methodology, playbooks, and standards by sharing what works, refining approaches based on delivery experience, and offering perspective in team methodology discussions.

• Apply established value measurement approaches to evaluate initiatives; contribute lessons learned to inform framework refinement by senior peers.

• Stay current with AI, machine learning, and emerging analytics developments relevant to the specialty area; bring learnings back to the team.

• Embed data quality, lineage, and integrity considerations into initiatives from the start, partnering with the Data Integrity team on standards and enterprise practices.

• **Influence & Stewardship

• Mentor less experienced Partners (Standard, Associate) 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 across the function to align on practitioner-level coordination and share lessons across teams.

• Model a collaborative, evidence-driven culture that reflects enterprise values; contribute to psychological safety and openness within the team.

• Support Lead and Principal Partners in preparing communications, artifacts, and materials for executive and governance forums.

• Contribute to enterprise data literacy and AI literacy by translating specialty depth into accessible guidance for clinicians, operational leaders, and analytics peers.

• Champion continuous improvement by questioning assumptions on initiatives, running structured retrospectives, and applying learnings forward. • Must be able to perform the professional, clinical and or technical competencies of the assigned unit or department.

• These statements are intended to describe the essential functions of the job and are not intended to be an exhaustive list of all responsibilities. Skills and duties may vary dependent upon your department or unit. Other duties may be assigned as required.

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