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.    

Primary Responsibilities:

• 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 Science, Statistics, or related field; Master's/PhD
• 7+ years in data science/ML/AI, ideally in healthcare
• Experience in healthcare AI domains: NLP, computer vision, predictive modeling
• Knowledge of generative AI nd LLMs (GPT, BERT, Llama)
• Familiarity with big data tools, SQL/NoSQL databases
• Understanding of healthcare standards (HL7, FHIR) and cloud platforms (AWS/ Azure/ GCP)
• Proficiency in Python, R, Java, or Scala
• Proven expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn)
• Proven solid statistical analysis and data visualization skills
• Proven excellent problem-solving and communication skills
• Proven track record of delivering AI/ML projects
• Model Development: Proven ability to design, develop, and deploy ML models and AI systems for healthcare challenges
• Data Analysis: Proven ability to interpret complex healthcare datasets to generate actionable insights
• Collaboration: Proven ability to work with clinicians, researchers, and IT teams to translate business needs into technical solutions
• Algorithm Design: Proven ability to implement advanced algorithms for predictive analytics, patient risk stratification, and medical image analysis
• Generative AI & LLMs: Proven ability to develop and integrate generative AI models and large language models for tasks like medical text generation and synthetic data creation
• Optimization: Proven ability to enhance existing ML models for scalability and performance
• Mentorship: Proven ability to guide junior data scientists and engineers
• Compliance: Proven ability to ensure data integrity and adhere to healthcare regulations (e.g., HIPAA)
• Communication: Proven ability to present findings through reports, presentations, and visualizations

At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.