Data & AI Enablement Lead
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IT/Tech
Job Description & How to Apply Below
The Data & AI Enablement Lead is a strategic individual contributor who partners with Finance, IT, and cross-functional stakeholders to translate complex business needs and data into actionable analytics and AI-enabled solutions. The role will shape Data & AI strategy and adoption; where the Data & AI Enablement Lead will lead and/or facilitate the following activities: evaluate and advance high-value use cases, facilitate delivery from discovery through adoption, communicate recommendations to diverse audiences, and promote responsible AI through effective governance, risk management, monitoring, and compliance.
Key ResponsibilitiesData & AI strategy and roadmap: Partner with business and technology leaders to define AI priorities, identify capability gaps, develop roadmaps, and align investments with measurable business outcomes.
Use-case identification and facilitation: Lead workshops and intake discussions to identify, assess, prioritize, and shape AI and advanced analytics opportunities based on value, feasibility, data readiness, risk, and scalability.
Data & AI governance and responsible use: Help establish and operationalize AI governance standards, decision rights, review processes, documentation requirements, and controls throughout the AI lifecycle.
Risk assessment and oversight: Coordinate with Legal, Compliance, Privacy, Security, Data Governance, and other stakeholders to evaluate model risk, bias, explainability, data quality, privacy, security, and regulatory considerations.
Solution development and delivery: Provide technical leadership for the design, testing, validation, implementation, and monitoring of machine learning, generative AI, and other AI-enabled solutions.
Business and technical support: Advise teams on appropriate AI methods, tools, platforms, data requirements, prompt design, model selection, testing approaches, and implementation options.
Performance monitoring: Define success measures and support ongoing monitoring of solution accuracy, reliability, adoption, risk, and business impact; recommend remediation or retirement when appropriate.
AI adoption and enablement: Develop guidance, reusable assets, training, and communications that improve AI literacy and promote consistent, secure, and responsible adoption across the organization.
Stakeholder communication: Translate complex AI concepts, risks, and findings into clear recommendations for business leaders, governance forums, and technical teams.
Continuous improvement: Stay current on emerging AI capabilities, industry practices, and evolving standards, and recommend practical improvements to the organization’s AI operating model.
Required Qualifications
Bachelor's degree and 5+ years of analytics experience or Master's degree and 3+ years of analytics experience.
Demonstrated ability to serve as a consultative analytics partner, working directly with business stakeholders to define problems, evaluate opportunities, and deliver actionable recommendations.
Experience leading projects through the full analytics/AI lifecycle, including business intake, discovery, analysis, solution development, communication of insights, and implementation support.
Experience using SQL, Power BI, Databricks, Python, or similar tools to support business decision-making.
Advanced degree in Informatics, Analytics, Business Analytics, Healthcare Analytics, Statistics, Computer Science, Data Science or a related field.
Progressive experience in financial analytics, business intelligence, Artificial intelligence informatics, or a related field.
Experience working with financial, accounting, claims, pharmacy, payer, provider, sales, or…
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