Director, Artificial Intelligence and Impact Science

L.A. Care Health Plan•Los Angeles, CA

About The Position

The Director of Artificial Intelligence (AI) and Impact Science is a senior leader, responsible for overseeing and advancing Applied AI and Casual Impact work. This position ensures that the team’s predictive, AI-driven, and causal analytics work is high-quality, reproducible, and aligned with the organization’s enterprise strategy and operational priorities. This Director bridges advanced technical expertise, strategic foresight, and cross-functional collaboration. Provides leadership and mentorship to staff, ensuring compliance with analytic development standards, governance policies, and reproducibility requirements. Additionally, this position maintains close alignment with Enterprise Analytics leadership, including Directors and Managers of domain-aligned analyst teams, to integrate the team’s outputs into broader portfolio initiatives and operational workflows. The Director scans the AI and emerging technology landscape to evaluate new solutions to guide build vs. buy decisions and ensure the organization continuously leverages innovative tools that provide incremental enterprise value. This position is responsible for directing all aspects of running an efficient team, including hiring, supervising, coaching, training, disciplining, and motivating direct reports.

Requirements

Master's Degree In lieu of degree, equivalent education and/or experience may be considered.
At least 7 years of progressive experience in advanced analytics, data science, or AI/ML.
At least 7 years of experience supervising/managing staff.
At least 3 years of professional experience working in a healthcare setting (e.g., Managed Care Organization, health system, hospital network, or health plan).
Demonstrated successful experience leading teams of technical practitioners (data scientists, analysts, or equivalent) in healthcare or complex enterprise environments.
Hands-on experience with AI/ML model development, causal inference, and enterprise-scale analytics projects.
Experience managing multiple projects and prioritizing resources in a dynamic environment.
Experience evaluating emerging AI and analytics technologies and guiding build vs. buy decisions.
Prior experience setting standards for reproducibility, governance, and responsible AI practices.
Demonstrated ability to think long-term and develop strategies that align with the overall goals of the organization.
Demonstrated ability to make sound and timely decisions.
Demonstrated ability to adapt to changing situations and adjust strategies accordingly.
Demonstrated ability to adapt to a fast-paced and evolving environment and to lead others through change.
Excellent interpersonal skills for building relationships, fostering teamwork, and creating a positive work environment.
Excellent written and verbal communication, negotiation, and interpersonal skills.
Excellent ability and knowledge in analyzing data, identifying problems, and making informed decisions, often in complex or ambiguous situations.
Demonstrated ability to lead and mentorship of technical teams in AI, data science, or analytics.
Ability to operationalize analytics and AI outputs into business workflows and enterprise decision-making.
Advanced understanding of predictive modeling, AI/ML methods, causal inference, and analytic pipeline design.
Strong project management and prioritization skills, including using Jira or equivalent workflow tools.
Expertise with collaboration and documentation tools such as GitHub and Confluence.
Exceptional communication and stakeholder engagement skills for technical and non-technical audiences.
Proven ability to collaborate across multiple business domains, integrating analytics into strategic decision-making and operational workflows.
Strong communication skills with the ability to translate complex technical topics for senior leadership and non-technical stakeholders.

Nice To Haves

Doctorate Degree
Experience in a Managed Care Organization (Medicaid, Medicare, ACA Exchange).
Experience with health equity analytics and population segmentation for targeted interventions.
Certified Health Data Analyst (CHDA)
Certified Analytics Professional (CAP)
Snowflake SnowPro Core Certification
SnowPro Specialty: Data Engineering or Snowpark
Health Economics and Outcomes Research (HEOR) Certification or Graduate Certificate
Advanced AI/ML or Data Science certifications (e.g., Microsoft DP-100, MITx MicroMasters in AI, or similar)
Expertise in responsible AI principles, including fairness, transparency, and explainability.
Ability to evaluate emerging AI technologies and integrate them strategically into enterprise analytics capabilities.
Knowledge of Shiny, Streamlit, or other visualization and analytic tool deployment platforms.
Knowledge of healthcare administrative datasets (claims, encounters, eligibility, provider networks, quality measures).
Knowledge of Snowflake/Snowpark, cloud-based analytics, and large-scale distributed computing environments

Responsibilities

Lead, mentor, and develop assigned team(s), fostering technical excellence, analytic rigor, and professional growth.
Ensure all analytic solutions follow standardized development practices, including version control, peer review, reproducible pipelines, and documentation protocols.
Serve as the primary liaison to other Enterprise Analytics leaders, integrating AI and causal science deliverables into domain-specific portfolios to maximize enterprise impact.
Guide cross-functional teams in translating AI and causal insights into actionable business recommendations, operational improvements, and strategic decision-making.
Oversee the design, implementation, and validation of predictive models, AI solutions, and causal impact studies, ensuring methodological rigor, scalability, and interpretability.
Establish and maintain technical standards, workflows, and governance policies for AI and causal impact analytics.
Continuously scan the AI, machine learning, and emerging technology landscape to identify tools, platforms, and frameworks that could enhance analytic capabilities, inform build vs. buy decisions, and deliver incremental value.
Assess new technologies and provide recommendations on integration strategies, feasibility, and potential Return on Investment (ROI) for adoption in enterprise workflows.
Promote the use of responsible AI principles, ensuring fairness, transparency, and explainability in all deployed solutions.
Maintain oversight of resource allocation, project prioritization, and delivery timelines across the team.
Collaborate with key stakeholders to integrate predictive and causal insights, providing holistic, enterprise-level solutions.
Represent the AI & Impact Science team to senior leadership and external stakeholders, communicating strategic value, project outcomes, and future opportunities.
Foster a culture of continuous learning, experimentation, and innovation within the team.
Proactively initiate, build and maintain effective relationships and communication with both internal and external key stakeholders. Communicate with senior leadership and executives, provide reports on performance and progress towards objectives.
Develop goals, objectives and action plans for assigned staff which includes full management responsibility for the hiring, performance reviews, salary reviews, training, and disciplinary matters for direct reports.
Conduct strategic planning for resource management in order to meet current and future departmental and enterprise-wide goals.
Develops, and manages department budget, monitors expenditures and ensures financial sustainability.
Perform other duties as assigned.