Data Scientist IV

This is a fully remote position, open to applicants in United States.

📋 Description

• Oversee the implementation of AI and machine learning solutions, guiding them from prototype to scalable production deployment.

• Set technical standards, conduct design reviews, and establish best practices and reusable frameworks for AI, machine learning, and advanced analytics.

• Create, develop, and manage predictive modeling, machine learning, and statistical solutions utilizing claims, EHR/EMR, laboratory, utilization management, clinical, and operational datasets.

• Execute data cleansing, feature engineering, exploratory data analysis, and generate actionable insights.

• Design, develop, test, deploy, and govern Generative AI, Agentic AI, NLP, deep learning, and RAG solutions following MLOps and LLMOps practices.

• Assess new AI technologies and propose enterprise adoption strategies based on business value, risk, and scalability.

• Ensure compliance with HIPAA/PHI regulations and work with privacy, security, and compliance teams to mitigate AI-related risks.

• Collaborate with clinical leadership, risk adjustment, care management, operations, IT, and analytics teams to prioritize tasks, define KPIs, communicate results, trade-offs, and progress on the roadmap.

• Act as an enterprise subject matter expert in AI, machine learning, and advanced analytics.

• Mentor data scientists and actively contribute to the development of innovative AI and machine learning capabilities.

• Perform additional job-related duties as assigned.

⛳️ Requirements

• A Bachelor's degree in Data Science, Mathematics, Statistics, Engineering, Computer Science, or a related field is required.

• Equivalent years of relevant work experience may substitute for the required education.

• A minimum of eight (8) years of experience in predictive analytics, data science, or a related field is required.

• At least three (3) years of experience in technical leadership, solution ownership, or mentoring is required.

• One (1) year of experience with cloud services such as Azure, AWS, or GCP, and modern data stacks like Databricks or Snowflake is required.

• Three (3) years of experience in delivering LLM and/or generative AI solutions from prototype to production is required.

• Expert knowledge of predictive modeling, machine learning, deep learning, NLP, generative AI, and healthcare analytics methodologies is essential.

• Expertise in Agentic AI, LLMs, prompt engineering, RAG, evaluation methodologies, and scalable trustworthy AI solutions is required.

• In-depth knowledge of transformer architectures, deep learning frameworks, and generative modeling concepts is essential.

• Familiarity with AI-powered document intelligence, OCR, language extraction, annotation, retrieval, and review workflows is preferred.

• Knowledge of MLOps/LLMOps practices, including CI/CD, experiment tracking, model and prompt versioning, automated testing, monitoring, observability, and reproducible pipelines is important.

• Understanding of AI governance, responsible AI, privacy-by-design, HIPAA/PHI handling, model risk management, prompt injection safeguards, and data leakage prevention is necessary.

• Expert knowledge in SQL and a working understanding of data modeling, data quality, and feature engineering for large healthcare datasets is required.

• Familiarity with healthcare operations, payer and provider models, and industry trends is expected.

• Knowledge of CPT-4, HCPCS, ICD-9/10, DRG, and Revenue Codes is essential.

• Understanding of managed care is required.

• Strong analytical, problem-solving, critical-thinking, written, verbal communication, and presentation skills are necessary.

• Strong project/program leadership abilities are important.

• Willingness to travel as needed by business requirements.

🏝️ Benefits

• A bonus linked to company and individual performance may be available.

• A comprehensive total rewards package is offered.

• Employee total well-being support is provided.