Sr. Data Scientist( Python,SQL, PyTorch, Tensorflow)
About The Position
Optum Payment Integrity Decision Intelligence is seeking a Senior Data Scientist for a high-impact, six-month contract focused on practical AI and machine learning solutions that improve efficiency, prioritization, and medical cost savings within Payment Integrity operations. The contractor will work with a mature, collaborative team of six AI engineers with experience in Agentic AI and large language models. The role is fully remote and offers autonomy, technical depth, and a focus on efficient delivery. The position involves developing and deploying statistical and machine learning models, including traditional predictive approaches, deep learning, LLMs, retrieval-augmented generation (RAG), and agentic workflows. The Senior Data Scientist will work with Data Scientists, Payment Integrity Operations leadership, data stewards, and engineering teams to define analytical objectives, prepare data, build end-to-end modeling pipelines, and translate results into actionable business insights. The role also includes documenting work for reproducibility and auditability, and continuously evaluating and improving model performance and agentic workflows.
Requirements
- Advanced degree in Applied Mathematics, Physics, Computer Science, Statistics, or a related technical field.
- Proficiency in traditional machine learning and statistical modeling, including regression, classification, and sampling design.
- Strong coding skills in Python, SQL, and related languages.
- Systems-level thinking and a track record of creative problem-solving, including non-standard approaches to complex challenges.
- Experience transitioning projects from proof of concept to production, with a focus on scalability, reliability, and performance.
- Exposure to LLM technologies.
Nice To Haves
- Knowledge of US healthcare data, such as claims, clinical records, authorization, or provider contracts.
- Proficiency in deep learning frameworks such as PyTorch or TensorFlow.
- Experience with Agentic AI frameworks such as LangChain, LlamaIndex, and other orchestration tools for autonomous agents.
- Hands-on experience implementing or adapting published academic research into practical solutions.
- Ability to understand emerging prompting strategies and research and evaluate their benefits and trade-offs.
Responsibilities
- Design and deploy intelligent models using statistical techniques, traditional machine learning, deep learning, LLMs, RAG, and Agentic AI.
- Use libraries and frameworks to develop scalable, production-grade solutions aligned with enterprise deployment standards.
- Lead cross-functional discovery sessions with Data Scientists and Payment Integrity Operations leadership to turn business challenges into analytical objectives.
- Align statistical rigor with emerging AI capabilities to maximize operational impact.
- Deliver statistical analyses that clearly frame business scenarios and inform decisions and process improvements.
- Collaborate with data stewards and engineering teams to curate high-quality datasets and ensure data integrity and readiness.
- Develop end-to-end modeling pipelines, including sampling design, data selection, and choice of statistical and AI methodologies.
- Document processes and results to support transparency, reproducibility, and auditability across ML and LLM-based systems.
- Communicate insights and model outputs to stakeholders as actionable business narratives.
- Continuously evaluate and refine model performance, incorporating feedback loops and adaptive learning mechanisms.
- Recommend improvements to algorithms and agentic workflows to generate insights and measurable improvements.
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What This Job Offers
Career Level
Senior
