Director Data Analytics

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.

As Director, Data Science, this leader will oversee the Payment Integrity Decision Intelligence (PIDI) Data Science and AIML Analytics India team, driving data science and AI-led innovation, analytical excellence and strategic transformation to deliver measurable business value across clinical and non-clinical payment integrity programs through a high-performing team of data science and AIML experts

The leader will champion a culture of innovation, scientific rigor and continuous improvement while establishing best practices for model development, validation, monitoring, performance optimization and building solid relationships with global analytics and data science teams

Also responsible for advancing the PI organization's analytical capabilities through the development, refinement and deployment of predictive and prescriptive models that uncover actionable opportunities and generate measurable business value

Primary Responsibilities

Lead Data Science and AIML India team, defining the vision, strategy, priorities and execution roadmap for AI, Machine Learning and Advanced Analytics initiatives that drive payment integrity outcomes and measurable business value across clinical and non-clinical value streams

Build, mentor and develop a high-performing team of Data Scientists and AIML experts, fostering a culture of innovation, technical excellence, continuous learning, scientific rigor, accountability and business impact

Provide strategic Data Science and AI leadership, partnering across business, operations, clinical, product and technology organizations to support broader PIDI data science strategy, identify high-value opportunities, influence key decisions and deliver scalable analytical solutions that drive measurable business outcomes

Drive the end-to-end development and evolution of Payment Integrity data science and AIML capabilities, including predictive and prescriptive models, advanced detection engines and analytical solutions that identify Fraud, Waste, Abuse and Error (FWAE) opportunities, outliers or aberrant billing patterns, overpayments and gaps and leakage opportunities across clinical and non-clinical programs

Serve as a hands-on technical leader and trusted advisor, providing oversight across the full AIML lifecycle, including problem formulation, data exploration, feature engineering, model development, validation, deployment, monitoring, governance and continuous improvement

Establish robust model performance, governance and value realization frameworks, including success metrics, monitoring strategies, financial impact assessment, model validation and optimization processes to ensure sustainable business outcomes and maximize savings opportunities

Champion the application of advanced analytics and AI methodologies, including machine learning, deep learning, predictive and prescriptive analytics, anomaly detection, simulation and statistical modeling to solve complex healthcare and payment integrity challenges

Lead applied research, innovation and modernization efforts, continuously evaluating emerging fraud and abuse patterns, next-generation AI technologies and advanced analytical techniques, while translating research and experimentation into scalable, production-ready solutions that enhance detection accuracy, operational efficiency and business performance

Establish and govern Responsible AI practices, including Data Compliance, AIRB approvals, model risk management, explainability, guardrails and human-in-the-loop oversight to ensure safe, compliant, ethical and business-aligned deployment of AIML solutions

Stay at the forefront of advancements in Data Science, AIML, Healthcare Analytics and Payment Integrity, identifying opportunities to leverage emerging technologies, strengthen organizational capabilities and drive innovation and

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

Graduate (Master's/PhD) degree in Engineering, Mathematics, Statistics, Computer Science, Artificial Intelligence, or related quantitative disciplines

15+ years of experience in Data Science, Advanced Analytics, AIML and predictive modeling, with at least 10+ years leading mid-sized, cross-functional teams

15+ years of hands-on programming experience using Python, R, SAS, SQL and distributed computing frameworks, in conducting statistical, research-minded analysis of variety of data types/forms with aim to utilize this analysis into building or optimizing predictive methods

10+ years of deep, hands-on experience with machine Learning applied to the healthcare or other high-stakes domains (direct experience in a cloud environment is highly valued)

Proven experience designing and delivering enterprise-scale AIML solutions from concept through production deployment and business adoption

Solid experience with cloud-based AIML platforms such as Azure AI, Azure Databricks or equivalent

Deep expertise in Machine Learning, Statistical Modeling, Deep Learning, Natural Language Processing (NLP) and Generative AI technologies

Solid understanding of MLOps, Model Governance, Responsible AI, Model Monitoring and AI Risk Management and AIRB frameworks

Proven ability to partner with executive leadership and business stakeholders to translate complex business problems into scalable AI solutions

Proven solid communication, stakeholder management and executive presentation skills with the ability to influence senior leadership decisions

Preferred Qualifications

Experience leading Generative AI, Large Language Models (LLMs), Agentic AI, Copilot, Retrieval-Augmented Generation (RAG), AI Automation initiatives, ML engineering tools and frameworks such as TensorFlow, PyTorch, Hugging Face, LangChain, LangGraph

Experience with AIML system design, solution architecture, enterprise integration patterns, APIs and microservices-based deployments

Experience in deploying machine learning models at scale with CI/CD, automated monitoring, observability and model lifecycle management

Experience leading AI-driven product development, innovation programs and research-to-production initiatives

Experience in Lean Six Sigma (Green belt/Kaizen)

Solid knowledge of data platforms and big data technologies including Snowflake, Databricks, Spark, Synapse Analytics, Microsoft Fabric and Hadoop ecosystems

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.