Data Scientist 2

Optum Insight is improving the flow of health data and information to create a more connected system. We remove friction and drive alignment between care providers and payers, and ultimately consumers. Our deep expertise in the industry and innovative technology empower us to help organizations reduce costs while improving risk management, quality and revenue growth. Ready to help us deliver results that improve lives? Join us in making healthcare work better for everyone through people-led, responsible AI while Caring. Connecting. Growing together.

Optum Insight COE Advanced Analytics team is seeking an experienced, hands-on Data Scientist 2 to design, develop, deploy, and support enterprise-grade analytics, ML, Gen AI, and Agentic AI solutions for complex healthcare and operational use cases. The successful candidate will combine solid foundations in data science, AI engineering, statistics, Python, SQL, machine learning, and cloud engineering with practical experience taking solutions from business problem definition and experimentation through production deployment, monitoring, and continuous improvement.

This role works closely with healthcare domain experts, product owners, data engineers, application engineers, platform teams, architects, and business stakeholders. The portfolio includes predictive and prescriptive analytics, patient-flow and operational forecasting, healthcare performance improvement, MLOps, model monitoring, natural-language analytics, Retrieval-Augmented Generation, multi-agent applications, and Responsible AI.

Primary Responsibilities

Translate complex healthcare, clinical, operational, and financial business problems into well-defined analytical questions, hypotheses, metrics, and solution designs

Design, develop, evaluate, and optimize machine learning models for classification, regression, time-series forecasting, recommendation, and predictive/prescriptive use cases

Design and implement enterprise-grade Generative AI applications using large language models, embeddings, Retrieval-Augmented Generation (RAG), vector retrieval, prompt engineering, and multi-agent workflows

Develop Agentic AI and multi-agent workflows involving routing, planning, tool invocation, memory, reflection, and supervisor-worker orchestration

Implement guardrails, validation, traceability, access controls, and human-review mechanisms for enterprise AI solutions

Own the end-to-end lifecycle of machine learning and AI solutions, moving models from experimentation through testing, deployment, MLOps, monitoring, drift detection, and continuous improvement

Build and maintain scalable data-processing workflows, feature tables, Delta tables, and model pipelines using Python, SQL, Spark, and Databricks

Apply software-engineering practices including modular code design, Git-based version control, automated testing, code reviews, logging, and technical documentation

Apply statistical methods, hypothesis testing, and experimental design to structured and unstructured healthcare data, ensuring clear differentiation between correlation and causation

Ensure compliance with Responsible AI practices, including fairness evaluation, explainability, hallucination assessment, output validation, and secure handling of sensitive healthcare data

Partner with cross-functional technical and business stakeholders to break complex work into user stories, technical milestones, architectural designs, and actionable analytical findings

You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications

• 2+ years of professional experience delivering Data Science, Machine Learning, Time Series forecasting, AI Engineering for production grade solutions
• 2+ years of hands-on proficiency in Python for data analysis, model development, application integration, and production engineering
• 2+ years of experience with SQL, including complex joins, aggregations, window functions, data validation, query optimization, and analytical dataset creation
• 2+ years of experience using machine learning libraries such as scikit-learn, XGBoost, PyTorch, or TensorFlow, Seaborn, Scikit-learn, MLflow
• 2+ years of experience with distributed computing and cloud platforms (e.g., Apache Spark/PySpark, Azure, Azure Databricks)
• 1+ years of experience with APIs, application integration, Git, automated testing, CI/CD pipelines, and production support practices
• Ability to leverage statistical and analytical techniques, including probability, hypothesis testing, regression, model evaluation, and experimental methods, to develop and evaluate robust solutions
• Experience with model-performance monitoring, data-quality checks, data drift, model drift, logging, and troubleshooting
• Ability to explain individual technical contributions, architectural decisions, implementation challenges, and measurable outcomes
• Demonstrated experience operationalizing and deploying models to production beyond proof-of-concept stages

Preferred Qualifications

Experience delivering healthcare analytics or AI solutions in clinical operations, population health, patient flow, utilization, or financial performance domains

Deep experience with Azure Databricks capabilities (Unity Catalog, Delta Lake, Workflows, Model Serving, MLflow, Databricks Apps, or Asset Bundles)

Hands-on experience developing LLM, Retrieval-Augmented Generation (RAG), semantic search, vector retrieval, or Agentic AI applications using tools such as LangChain, LangGraph, or Semantic Kernel

Experience building REST APIs (FastAPI or Flask) and containerized deployments using Docker or Kubernetes

Familiarity with Responsible AI practices, model interpretability, bias assessment, AI safety, and privacy-preserving analytics in regulated healthcare environments

Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $72,800 - $130,000 annually based on full-time employment. We comply with all minimum wage laws as applicable.

At UnitedHealth Group, our mission is to help people live healthier lives and help make the health system work better for everyone. Together, we are shaping the future of healthcare by harnessing technology and innovation to make care simpler to navigate, more affordable and more connected for the people we serve. We are committed to creating an inclusive workplace where everyone feels welcomed, valued, heard and respected, empowering people to bring their authentic selves to work and strengthening our collective impact through diverse talents, backgrounds, experiences and perspectives.

UnitedHealth Group and its affiliated brands are an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.

UnitedHealth Group and its affiliated brands are a drug-free workplace. Candidates are required to pass a drug test before beginning employment.