Lead Data Scientist

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.

Design, develop, and deploy advanced ML/AI models for healthcare applications, ensuring rigor across feature engineering, training, evaluation, and explainability Analyze complex healthcare datasets to deliver actionable insights, applying statistical modeling, time‑series forecasting, survival analysis, and other advanced analytics techniques Lead the development of production‑grade ML solutions with robust, scalable, and maintainable Python/SQL code, ensuring proper versioning, monitoring, and model performance governance Collaborate with clinicians, researchers, data engineers, and product/IT teams to translate business and clinical needs into high‑impact, domain‑aware ML solutions Develop and optimize models using Scikit‑learn, PyTorch, and modern deep learning architectures, including support for pre‑GenAI and GenAI approaches Integrate and evaluate generative AI and LLM‑based capabilities for tasks such as summarization, medical text generation, synthetic data creation, and assisted clinical reasoning Build and enhance RAG pipelines using vector databases (FAISS, Pinecone, Chroma) while optimizing retrieval accuracy, grounding, and model responses Apply knowledge graph techniques to model entity relationships and support reasoning‑based analytics using healthcare ontologies Ensure models follow healthcare data standards (FHIR, HL7, ICD, CPT, SNOMED, LOINC, NDC) for compliance, safety, and interoperability Optimize existing models for performance, scalability, and robustness, including drift detection, A/B testing, and continuous monitoring Lead model governance activities including documentation, model cards, quality reviews, validation protocols, and Responsible AI best practices Communicate insights and results through clear reports, visualizations, presentations, and technical narratives tailored to technical and clinical stakeholders Mentor data scientists, provide technical direction on experimentation, solution design, and coding best practices, and drive a culture of scientific rigor and innovation Work closely with data engineering teams to ensure high‑quality feature pipelines, clean transformations, and seamless ML integration into production systems Comply with company policies, employment terms, and organizational directives as required Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Eligibility To apply to an internal job, employees must meet the following criteria: Minimum 12 months in the current Role/Grade/Level Not on Active CAP at the time of applying for the IJP Employees currently at Grade 27 will move to the next grade and Grade 28 (Lateral Movement) can apply for this position Last Review rating of Meets Expectations or Exceeds Expectation Required Qualifications: Graduate degree or equivalent experience Bachelor's degree in CS, Data