Data Scientist IV

• Lead the operationalization of AI and machine learning solutions from prototype through scalable production deployment.
• Establish technical standards, design reviews, best practices, and reusable frameworks for AI, machine learning, and advanced analytics solutions.
• Stay current on the latest trends in LLMs, NLP, generative AI, and healthcare informatics, integrating relevant advancements into projects to drive continuous innovation.
• Design, develop, and oversee predictive modeling, machine learning, and statistical solutions using healthcare data sources including claims, EHR/EMR, laboratory, utilization management, and other clinical and operational datasets; ensure appropriate evaluation, calibration, monitoring, and interpretability.
• Conduct rigorous data analysis, including data cleansing, feature engineering, and exploratory data analysis, to derive meaningful insights and actionable recommendations.
• Design, develop, test, deploy, and govern advanced AI solutions including Generative AI, Agentic AI, NLP, deep learning, and retrieval-augmented generation (RAG) capabilities using established MLOps and LLMOps practices.
• Provide technical leadership in transitioning AI and machine learning solutions from prototype to scalable production deployment.
• Evaluate emerging AI technologies and recommend enterprise adoption strategies based on business value, risk, and scalability.
• Ensure compliance with HIPAA/PHI handling and internal governance standards; collaborate with privacy, security, and compliance partners to mitigate risks such as data leakage, prompt injection, and unsafe outputs.
• Collaborate with cross-functional stakeholders (clinical leadership, risk adjustment, care management, operations, IT, and analytics partners) to prioritize work, define KPIs, and communicate results, tradeoffs, and roadmap progress.
• Serve as a subject matter expert for AI, machine learning, and advanced analytics initiatives across the enterprise.
• Perform any other job related duties as requested.

• Bachelor's degree in Data Science, Mathematics, Statistics, Engineering, Computer Science, or other related field required
• Master's degree preferred
• Equivalent years of relevant work experience may be accepted in lieu of required education
• Eight (8) years of experience in predictive analytics, data science, or a related field, preferably within the healthcare industry or managed care organizations, required
• Three (3) years of technical leadership, solution ownership, or mentoring experience required
• One (1) year of experience with cloud services (such as Azure, AWS or GCP) and modern data stack (such as Databricks or Snowflakes) required
• Three (3) years of experience delivering LLM and/or generative AI solutions (e.g., prompt engineering, fine-tuning approaches, and/or RAG) from prototype through production required

• Technical leadership skills including mentoring, solution architecture, technical review, and ability to influence across cross-functional teams
• Expert knowledge of predictive modeling, machine learning, deep learning, NLP, generative AI, and healthcare analytics methodologies
• Expertise in modern AI architectures including Agentic AI, Large Language Models (LLMs), prompt engineering, Retrieval-Augmented Generation (RAG), evaluation methodologies, and techniques for building scalable, trustworthy AI solutions
• Expert knowledge of transformer architectures, deep learning frameworks, and generative modeling concepts, including quality, latency, scalability, and cost tradeoffs
• Familiarity with designing and deploying AI-powered document intelligence, OCR, language extraction, annotation, retrieval, and review workflows utilizing modern NLP, LLM, and Agentic AI technologies
• Familiarity with MLOps/LLMOps practices including CI/CD, experiment tracking, model and prompt versioning, automated testing, monitoring, observability, and reproducible pipelines
• Understanding of AI governance and responsible AI, including privacy-by-design, HIPAA/PHI handling, model risk management, and safeguards against prompt injection and data leakage
• Expert knowledge in SQL and working knowledge of data modeling, data quality, and feature engineering for large healthcare datasets
• Knowledge of healthcare operations, payer and provider models, and industry trends
• Excellent analytical, problem-solving, and critical-thinking skills, including the ability to translate complex data into actionable insights
• Strong project/program leadership skills
• Excellent written and verbal communication and presentation skills
• Knowledge of health care coding including CPT-4, HCPCS, ICD-9/10, DRG and Revenue Codes
• Knowledge of managed care required

• None

• General office environment; may be required to sit or stand for extended periods of time
• Ability to travel as required by the needs of the business.

Compensation Range:

CareSource takes into consideration a combination of a candidate’s education, training, and experience as well as the position’s scope and complexity, the discretion and latitude required for the role, and other external and internal data when establishing a salary level. In addition to base compensation, you may qualify for a bonus tied to company and individual performance. We are highly invested in every employee’s total well-being and offer a substantial and comprehensive total rewards package.

Compensation Type (hourly/salary):

Organization Level Competencies

• Fostering a Collaborative Workplace Culture

• Cultivate Partnerships

• Develop Self and Others

• Drive Execution

• Influence Others

• Pursue Personal Excellence

• Understand the Business

This job description is not all inclusive. CareSource reserves the right to amend this job description at any time. CareSource is an Equal Opportunity Employer. We are dedicated to fostering an environment of belonging that welcomes and supports individuals of all backgrounds.