About this role
Salary Range: $117,509.00 (Min.) - $152,762.00 (Mid.) - $188,015.00 (Max.)
Established in 1997, L.A. Care Health Plan is an independent public agency created by the state of California to provide health coverage to low-income Los Angeles County residents. We are the nation’s largest publicly operated health plan. Serving more than 2 million members, we make sure our members get the right care at the right place at the right time.
Mission: L.A. Care’s mission is to provide access to quality health care for Los Angeles County's vulnerable and low-income communities and residents and to support the safety net required to achieve that purpose.
Job Summary
The Applied Artificial Intelligence (AI) Scientist II plays a critical role in advancing the organization’s enterprise strategy through the innovative use of Artificial Intelligence and Machine Learning (AI/ML). This position supports the health plan’s strategic goal to become a data-driven enterprise that uses advanced analytics to power decision-making, optimize operations, and improve health outcomes across all lines of business.
The Applied AI Scientist II is responsible for designing, developing, and deploying scalable predictive and AI solutions that address key enterprise challenges, such as improving claims payment integrity, predicting hospital readmissions, optimizing member quality outcomes, and identifying emerging risks. This position bridges advanced technical expertise with business impact, ensuring that AI solutions are not only accurate and explainable, but also integrated into daily operational workflows that drive measurable value.
Duties
Design, train, and validate predictive and AI models to support key strategic used cases throughout cross-functional Plan departments working with Information Technology to embed AI insights into decision workflows.
Partner with cross-functional key stakeholders to embed AI insights into decision workflows.
Implement production-ready models through MLOps pipelines, ensuring reproducibility, scalability, and continuous performance monitoring.
Apply responsible AI principles and maintain explainability in all deployed solutions.
Collaborate closely with the key stakeholders to ensure AI initiatives are tightly aligned with enterprise goals and transformation priorities.
Work closely with cross-functional key stake holders to ensure secure and efficient integration of AI assets into cloud and data platforms (e.g., Snowflake, Azure).
Clearly document model design, data assumptions, evaluation metrics, and production procedures.
Communicate complex analytic concepts in accessible, actionable terms for non-technical stakeholders.
Prepare written reports and visual presentations to convey insights and business implications effectively.
Stay current on emerging AI techniques, cloud technologies, and open-source frameworks relevant to healthcare analytics.
Experiment with generative AI, prompt engineering, and retrieval-augmented generation (RAG) to expand analytic capabilities.
Participate in peer reviews and contribute to continuous improvement of modeling standards and reusable assets.
Performs other duties as assigned.
Duties Continued
Education Required
Bachelor's Degree In lieu of degree, equivalent education and/or experience may be considered.
## Education Preferred
Master's Degree
## Experience
Required:
At least 6 years of professional data analytics experience in a professional environment.
At least 2 years of experience developing and deploying ML/AI solutions in a production or enterprise environment, preferably in the healthcare setting.
Proven experience applying AI/ML to real-world datasets, preferably in the healthcare industry.
Hands-on experience with supervised and unsupervised learning techniques, feature engineering, and model evaluation.
Experience operationalizing models in enterprise environments (e.g., through APIs, pipelines, or batch processes).
Preferred:
Experience within a Managed Care Organization (MCO) or health plan environment (Medicaid, Medicare, or ACA Exchange).
Experience with generative AI, Large Language Models (LLMs), and prompt engineering in practical use cases.
Experience with cloud-based MLOps environments (e.g., Azure ML, Snowpark, Databricks).
Experience with LLM-based solutions, prompt engineering, or generative AI in production use cases.
Skills
Required:
Advanced technical & data engineering skills.
Strong proficiency in Python (Pandas, Scikit-learn, PySpark) for data manipulation, modeling, and analytics.
Solid understanding of supervised and unsupervised machine learning methods, feature engineering, model evaluation, and validation techniques.
Ability to operationalize models in production environments, including basic MLOps practices (version control, CI/CD, reproducibility).
Ability to communicate complex AI/ML concepts effectively to non-technical stakeholders.
Excellent documentation skills, ensuring reproducibility, clarity of assumptions, and transparency of model design.
Strong collaboration skills, with proven ability to work cross-functionally with key stakeholders.
Analytical problem-solving skills with the ability to translate business challenges into actionable AI/ML solutions.
Effective written and verbal communication skills, including documentation of modeling processes, assumptions, and results.
Demonstrated collaboration skills, with experience working across technical and business teams to deliver practical, high-value AI solutions.
Preferred:
Knowledge of cloud-based AI platforms and MLOps environments within the Snowflake environment.
Knowledge of healthcare-specific data sets, including claims, encounters, provider data, quality metrics, or risk scores.
Knowledge of visualization and app deployment frameworks such as Shiny, Streamlit, or Power BI integrations.
Knowledge and understanding of responsible AI principles, including fairness, explainability, and bias detection.
Knowledge of healthcare data structures (claims, encounters, eligibility, provider, quality metrics).
Licenses/Certifications Required
Licenses/Certifications Preferred
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) or relevant certification
## Required Training
Physical Requirements
Light
## Additional Information
Salary Range Disclaimer: The expected pay range is based on many factors such as geography, experience, education, and the market. The range is subject to change.
L.A. Care offers a wide range of benefits including
- Paid Time Off (PTO)
- Tuition Reimbursement
- Retirement Plans
- Medical, Dental and Vision
- Wellness Program
- Volunteer Time Off (VTO)