AI Strategy Associate Director - State Health

** Job Family**  **:*
* Data Science Consulting

** Travel Required**  **:*
* Up to 10%

** Clearance Required**  **:*
* Ability to Obtain Public Trust

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* What You Will Do:

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* We are seeking an experienced AI and data practitioner to join our growing AI and Data practice with a dedicated focus on State Health agencies, with an emphasis on Medicaid programs and the responsible development and operationalization of AI solutions. This individual will be a hands-on leader who can connect strategy to execution, partnering with agency leaders to define high-value AI use cases, establish an enterprise AI strategy, and advance AI enablement across the organization.

This is a leadership role for someone who thrives at the intersection of state health mission outcomes, data and AI capabilities, and practical implementation. You will guide clients through the full lifecycle, from identifying and prioritizing use cases to designing the operating model, data foundations, governance, and delivery approach needed to move solutions into production.

The Associate Director will oversee cross-functional teams and work directly with client executives and program leaders to drive measurable value through AI, analytics, and modern data practices.

** Key Responsibilities Include*
* ** Client Leadership and Delivery*
* + Serve as a trusted advisor to State Health and Medicaid leaders on developing an AI strategy that covers:

+ Core enterprise AI capabilities (data readiness, governance, model lifecycle management, tooling)

+ Priority mission and operational use cases (member and provider experience, program operations, integrity, quality, and analytics)

+ Lead engagements from strategy through implementation, with a focus on outcomes, adoption, and sustainable operations.

+ Translate complex health and Medicaid business challenges into actionable AI/ML and analytics solutions using platforms such as Azure, AWS, GCP, Databricks, Snowflake, and related services.

+ Partner with IT, program, privacy, security, legal, and procurement stakeholders to support delivery that aligns to agency policies and applicable regulations.

** AI Strategy, Use Case Portfolio, and Roadmaps*
* + Facilitate use case discovery and prioritization workshops with stakeholders across agency divisions.

+ Define an AI use case portfolio and roadmap that balances:

+ Quick-win productivity use cases

+ Program modernization and longer-term transformation

+ Foundational capabilities (data, governance, operating model) needed to scale

+ Create pragmatic adoption plans including workforce readiness, change management, training, and communications.

** Solution Development and Operationalization*
* + Guide solution design and implementation for AI and GenAI capabilities, including:

+ Decision support and predictive analytics

+ Intelligent document processing, summarization, and search

+ Customer service and contact center augmentation

+ Caseworker support tools and workflow automation

+ Program integrity and anomaly detection

+ Lead and advise on production readiness topics such as model monitoring, drift, validation, human-in-the-loop workflows, and incident response procedures.

+ Partner with data engineering and architecture teams to design data pipelines and curated datasets that support trusted analytics and AI use.

** Data, Interoperability, and Medicaid Domain Enablement*
* + Apply Medicaid and state health data knowledge across domains such as:

+ Claims and encounters, eligibility and enrollment, provider data, managed care, long-term services and supports, pharmacy, behavioral health, and social determinants

+ Support data integration and interoperability approaches using standards and frameworks such as FHIR, HL7, and related health data exchange patterns where relevant.

+ Help teams define data quality, lineage, metadata, and access patterns that support scalable AI and analytics.

** Responsible AI, Governance, Privacy, and Security*
* + Establish practical AI governance approaches including intake, review, risk management, and approval pathways.

+ Incorporate responsible AI practices, transparency, auditability, and privacy-preserving approaches into delivery.

+ Collaborate with…