Scientist Python Jobs in Long Beach, CA (NOW HIRING)

Job Summary:
L.A. Care Health Plan is the nation’s largest publicly operated health plan, dedicated to providing health coverage to low-income residents in Los Angeles County. The Applied AI Scientist III is responsible for designing, building, and implementing advanced AI and ML solutions, leading complex projects, and collaborating with cross-functional teams to improve healthcare outcomes.
Responsibilities:
• 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.
• Ensure that the facts and details are correct so that the program's deliverable meets the needs of the department, organization and legislation's policies, standards, and best practices.
• Provide training, recommend process improvements, and mentor staff, department interns, etc. as needed.
• Perform other duties as assigned.
Qualifications:
Required:
• 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.
• 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)
Preferred:
• Doctorate Degree
• 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.
Company:
L.A. Care’s mission is to provide access to quality health care for L.A. Founded in 1994, the company is headquartered in Los Angeles, USA, with a team of 1001-5000 employees. The company is currently Late Stage.