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 productionize AI/ML and Generative AI solutions that improve healthcare operations, clinical decision support, and member experience
• Own end to end ML delivery, including problem framing, feature engineering, model training, evaluation, deployment, and post production monitoring
• Build and deploy models across use cases such as classification, forecasting, NLP, deep learning, and LLM based applications at production scale
• Implement and maintain MLOps / LLMOps best practices, including CI/CD pipelines, experiment tracking, model registries, automated retraining, and drift detection
• Ensure models meet performance, reliability, cost, and scalability requirements, supporting both batch and real time inference
• Champion engineering excellence, including unit testing, code reviews, documentation, and observability standards
• 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

Required Qualifications:

• Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related quantitative field; advanced degree preferred
• 8+ years of overall experience across AI/ML engineering, data engineering, and analytics roles, with demonstrated ownership of production grade ML systems
• Hands-on experience with BI and analytics tools, such as Power BI, Tableau, or equivalent enterprise BI platforms, including semantic models, KPIs, and analytical dashboards
• Solid hands-on experience designing, building, and deploying machine learning and generative AI solutions using Python based ML/DL frameworks (e.g., scikit learn, PyTorch, TensorFlow)
• Experience integrating AI/ML outputs into BI and decisioning workflows, including explainable insights, forecasting, and predictive metrics for business users 
• Proven experience across the end to end ML lifecycle, including data preparation, feature engineering, model training, evaluation, deployment, and monitoring (MLOps)
• Solid understanding of data modeling, metrics definition, and analytical layer design, enabling translation of business KPIs into ML ready features and AI driven insights
• Advanced proficiency in SQL and experience working with large scale analytical datasets in data warehouses or lakehouse environments

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.