Applied Artificial Intelligence Scientist III Job at L.A. Care Health Plan (Los Angeles)

Job Description

The Applied Artificial Intelligence (AI) Scientist III is a subject matter expert, hands-on practitioner who designs, builds, and implements advanced artificial intelligence (AI) and machine learning (ML) solutions that directly enable the organization to execute its strategic priorities. This role combines deep technical expertise with healthcare domain knowledge to deliver scalable, production-grade AI applications that improve quality, reduce administrative waste, and enhance member outcomes.

Job Responsibility

Design, train, validate, and deploy complex AI and ML models to address enterprise use cases across departments such as Health Services, Payment Integrity, Quality Improvement, Finance, and Provider Network Management
Lead all phases of the AI solution lifecycle – from problem framing and data engineering through model design, validation, and operational integration
Implement production-grade ML pipelines using modern MLOps practices, ensuring scalability, reproducibility, and continuous model performance monitoring
Serve as a subject matter expert in responsible and explainable AI, ensuring model fairness, transparency, and compliance with regulatory and ethical standards
Partner with business and technology leaders to identify and prioritize new AI use cases that align with the organization’s transformation strategy
Translate business challenges into well-structured analytical problems and lead cross-functional teams through data discovery, feature engineering, and algorithm development
Work directly with cloud-based data and AI platforms (e.g., Snowflake, Azure ML, Databricks) to operationalize model delivery and integration with enterprise data assets
Mentor and coach staff, providing technical guidance, code reviews, and knowledge sharing
Document all model design assumptions, data sources, evaluation metrics, and deployment protocols for transparency and reproducibility
Communicate complex technical results in accessible, actionable ways for both executive and operational stakeholders
Contribute to the development of reusable AI assets, libraries, and standardized templates to accelerate future model development
Remain current on emerging AI/ML technologies, frameworks, and healthcare analytics applications, and advise leadership on adoption opportunities
Apply subject matter expertise in evaluating business operations and processes
Identify areas where technical solutions would improve business performance
Consult across business operations, provide mentorship, and contribute specialized knowledge

Requirements

Master's Degree
At least 6 years of professional experience developing and deploying machine learning and AI solutions in enterprise or healthcare environments
Demonstrated experience leading full AI solution lifecycles – from problem definition to deployment and monitoring
Proven successful experience developing predictive models using structured and unstructured healthcare data (e.g., claims, encounters, eligibility, provider, quality metrics)
Experience with Python (Pandas, Scikit-learn, PySpark), distributed data frameworks (Spark), and MLOps concepts
Strong collaboration and mentorship experience, including guiding junior data scientists and analysts
Experience integrating AI solutions into production environments in collaboration with IT or Data Engineering
Experience with version control (Git) and model documentation best practices
Experience building and deploying models in production using MLOps frameworks and cloud platforms
Advanced programming skills in Python, including libraries for data processing, modeling, and analytics (e.g., Pandas, Scikit-learn, PySpark)
Deep understanding of machine learning and AI techniques, including supervised and unsupervised learning, feature engineering, model optimization, and explainability
Strong analytical problem-solving skills with the ability to structure complex problems into actionable modeling tasks
Exceptional written and verbal communication skills, including documentation and presentation of technical material to non-technical audiences
Excellent collaboration skills and ability to lead cross-functional projects involving IT, business stakeholders, and analytics peers
Excellent communication, documentation, and stakeholder engagement skills

Nice to have

Experience within a Managed Care Organization (MCO) or health plan environment (Medi-Cal, Medicare, or ACA Exchange)
Experience developing and operationalizing Large Language Models (LLM)-based solutions, including prompt engineering or retrieval-augmented generation (RAG)
Experience in risk adjustment, payment integrity, or quality measurement modeling
Experience with healthcare data analytics and modeling in Managed Care settings
Knowledge of generative AI tools and frameworks (e.g., LangChain, OpenAI APIs, Azure OpenAI)
Knowledge and understanding of responsible AI principles, including bias detection, fairness, and explainability
Knowledge of R or SQL for complementary analytics tasks
Knowledge of Snowpark for scalable model deployment
Knowledge of Shiny or Streamlit for AI-driven application delivery
Doctorate Degree
Snowflake SnowPro Core Certification
SnowPro® Specialty: Snowpark Certification
Python Institute PCEP™ or PCAP™ (Python Programming)
HarvardX or Johns Hopkins Data Science Certificate (R)
Microsoft Certified: Data Scientist Associate (DP-100)
Certified Analytics Professional (CAP)
Certified Health Data Analyst (CHDA)
Microsoft Certified Professional (MCP)

What we offer

Paid Time Off (PTO)
Tuition Reimbursement
Retirement Plans
Medical, Dental and Vision
Wellness Program
Volunteer Time Off (VTO)

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Applied Artificial Intelligence Scientist III

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