Note: The job is a remote job and is open to candidates in USA. Cotiviti is a healthcare technology company focused on reducing healthcare costs and improving health quality and outcomes. The Generative AI Scientist - Model Risk & Validation will conduct independent model validation, assess model and data drift, benchmark or rebuild models, and improve monitoring, governance, and responsible AI practices for generative AI and machine learning systems.
Responsibilities
- As a Generative AI Scientist within Cotiviti you will be responsible for delivering solutions that help our clients identify payment integrity issues, reduce the cost of healthcare processes, or improve the quality of healthcare outcomes. You will work as part of a team and will be individually responsible for the delivery of value associated with your projects
- Conduct independent model validation of existing models for benchmarking, assessment, and gauging effectiveness
- Determine aspects of model drift and related data drift for the purpose of model risk management (MRM) to both reduce risk and also find opportunities to drive new revenue growth and innovation. Apply deep expertise with AI/ML/GenAI model development, including hands-on experience with model building and model evaluation
- Benchmark and potentially rebuild existing models as needed using updated data, and potentially newer, more modern and effective algorithms
- Actively drive improvements in model monitoring activities, including methods for model registration, model metadata management, and conceptualizing approaches for related tools and techniques. Complete all responsibilities as outlined in the annual performance review and/or goal setting
- Complete all special projects and other duties as assigned
- Must be able to perform duties with or without reasonable accommodation
Skills
- Graduate Degree in a quantitative discipline such as Computer Science/Engineering, Statistics, Operations Research covering Advanced Statistics, Machine learning and AI
- Experience with the latest techniques in natural language processing including transformers, fine-tuning LLMs, measuring/benchmarking and deploying LLMs with tools such as HuggingFace, Langchain, LLAMA/Mistral and OpenAI, vector databases
- 1+ years of hands-on data science/AI experience, using typical machine learning and data science tools including pandas, scikit-learn, keras, nltk, and TensorFlow/PyTorch, GPU
- Experience building production-grade machine learning deployments on AWS, Azure, or GCP
- Experience working with Apache Spark™ and large-scale distributed datasets
- Experience communicating technical concepts to non-technical and technical audiences is a plus
- Passion for collaboration, learn it all mindset and driving value with AI
- Familiarity with healthcare payor ecosystem and related data
- General understanding of Responsible AI (RAI), including explainability (XAI), AI NIST RMF, and related AI risk management frameworks
- Experience and understanding evaluating models for bias and fairness, with aptitude for detecting bias in the model design and data, as well as using metrics such as SHAP and LIME
- Understanding appropriate model metrics and techniques for managing, evaluating and monitoring GenAI models and LLMs
- Understanding and familiarity with model governance and data governance best practices
- Strong understanding of technology systems for model development (e.g., Python, DataRobot, AWS Sagemaker), model deployments (AWS, Azure, DataRobot, DataBricks), model monitoring (AWS Model Monitor, MLFlow, NannyML, FiddlerAI, Arize) and related tools for model management and metadata management
Benefits
- Medical, dental, vision, disability, and life insurance coverage
- 401(k) savings plans
- Paid family leave
- 9 paid holidays per year
- 17-27 days of Paid Time Off (PTO) per year, depending on specific level and length of service with Cotiviti
- Remote work arrangement
Company Overview
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