Senior Staff Generative AI Scientist

Responsibilities

• Deliver solutions that help our clients identify payment integrity issues, reduce the cost of healthcare processes, or improve the quality of healthcare outcomes.
• Work as part of a team and be individually responsible for the delivery of value associated with your projects.
• Follow processes and practices that allow your models to be incorporated into our machine learning platform for production execution and monitoring.
• Work with key stakeholders within Research and Development as well as Operations, along with product management to assess the potential value and risks associated with business problems that have the potential to be solved using machine learning and Artificial Intelligence techniques.
• Develop an exploratory data analysis approach to verify the initial hypothesis associated with potential Artificial Intelligence/Machine Learning use cases.
• Document your approach, thinking and results in standard approaches to allow other data scientists to collaborate with you on this work.
• Prepare your final trained model and develop a validation test set for QA.
• Work with production operations to deploy your model into production and support them in monitoring model performance.
• Participate in other data science teams collaborating with your peers to support their projects.
• Participate in knowledge sharing sessions to bring new insights and technologies to the team.
• Participate in design sessions to continuously develop and improve the Cotiviti machine learning platform.
• Provide End to End value-based solutions, including data pipeline, model creation and application for end user consumption.

Qualifications

• PhD or 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.
• 9+ 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.
• Good to have publication record in journals/conferences and/or history of innovation.
• 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.