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.

Optum is seeking a Data Science professional who is passionate about applying machine learning, Generative AI, and Large Language Models (LLMs) to solve complex healthcare problems on a scale. Imagine working with massive volumes of healthcare data spanning clinical, claims, behavioral, and digital interactions-powering intelligent personalization, discovery, and decision support for millions of members, providers, and care teams.

At Optum, the Data Science mission is to transform healthcare data into robust, scalable AI solutions, including LLM‑based and Retrieval‑Augmented Generation (RAG) systems that combine enterprise knowledge with advanced language models to deliver accurate, contextual, and trustworthy insights. These solutions help uncover deep usage patterns, member journeys, and care signals that inform and continuously evolve Optum's digital products, clinical platforms, and healthcare services.

Your work will directly influence how healthcare consumers engage with digital experiences, how clinicians access timely insights, and how business and care strategies are shaped through data. By joining Optum's data science team, you will be part of an exciting journey to build advanced ML and GenAI‑driven products, grounded in responsible AI principles, that operate at enterprise scale and create meaningful impact across the healthcare ecosystem.

Primary Responsibilities:

• Design, develop, and deploy advanced analytics, machine learning, and Generative AI solutions to address complex healthcare and business problems using largescale structured and unstructured data
• Drives innovative data science solutions using large, complex, and unstructured datasets
• Applies advanced techniques including statistics, machine learning, simulation, and mathematical modelling
• Designs and delivers predictive and prescriptive models for optimal data value extraction
• Develops and evaluates advanced algorithms to enhance product and decision-making capabilities
• Utilizes tools such as Python, R, SQL, Hadoop, and analytics platforms for large-scale data processing
• Build and optimize LLM‑based applications, including Retrieval‑Augmented Generation (RAG) frameworks, to enable accurate, context‑aware, and explainable insights from enterprise healthcare data sources such as clinical notes, claims, provider data, and policy documents.
• Apply exploratory data analysis (EDA) and statistical techniques to understand data quality, bias, and limitations, ensuring responsible and reliable use of healthcare data in AI solutions.
• Collaborate with data engineers to design data pipelines and vector stores that support RAG architecture, embeddings, and efficient retrieval from internal knowledge bases.
• Develop, evaluate, and finetune machine learning and GenAI models, including prompt engineering, retrieval strategies, and model evaluation techniques to improve accuracy, relevance, and performance.
• Ensure responsible AI practices, including fairness, transparency, privacy, and compliance with healthcare regulations (e.g., HIPAA), when working with sensitive healthcare data.
• Translate complex analytical and GenAI outputs into clear, actionable insights for business stakeholders, product teams, and leadership to support data‑driven decision‑making.
• Support prototyping, validation, and deployment of GenAI and ML solutions, working with engineering teams to ensure solutions are scalable, secure, and maintainable. Continuously stay current with advancements in LLMs, GenAI frameworks, and healthcare AI trends, contributing innovative ideas and improvements to Optum's capabilities
• 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 regard 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 (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field)
• 5+ years of experience in handling/active development in data science projects
• 5+ years of experience in Microsoft Azure Cloud, Databricks, Mlflow, Spark SQL & Python
• Experience using Machine Learning Algorithms: Linear & Logistic Regression, Time Series analysis, Support Vector Machine, K-Means clustering, K-Nearest Neighbors Decision Trees, Random Forest, Naive Bayes, PCA, SVD, Artificial Neural Networks, Association Rules, Genetic Algorithm, Optimization, Bagging and Boosting algorithms etc.
• Proficient with hands-on experience in Python coding, Spark SQL and any other programming language along with corresponding language packages
• Understanding of data, schema, data model, machine learning and how to bring efficiency in big data related life cycle
• Proven skills to create opportunities using machine learning or artificial intelligence
• Proven excellent communication and presentation skills

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.