Optum Data Scientist Job Openings 2026 – Apply Soon!

Qualifications

Required Qualifications:

• Bachelor’s Degree (preferably in information technology, engineering, math, computer science, analytics, engineering or other related field)
• 4+ years of experience in handling/active development in data science projects
• 4+ 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.
• Understanding of data, schema, data model, machine learning and how to bring efficiency in big data related life cycle
• Proficient with hands-on experience in Python coding, Spark SQL and any other programming language along with corresponding language packages
• Proven skills to create opportunities using machine learning or artificial intelligence
• Proven excellent communication and presentation skills

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