Data Scientist

Position: Data Scientist 2
Job d:

Location:

Plymouth, Minnesota, United States Salary: $72,800 - $130,000/year

Job Area:
Business & Data Analytics Company:
United Health Group 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 solutions2+ years of hands-on proficiency in Python for data analysis, model development, application integration, and production engineering2+ years of experience with SQL, including complex joins, aggregations, window functions, data validation, query optimization, and analytical dataset creation2+ years of experience using machine learning libraries such as scikit-learn, XGBoost, PyTorch, or Tensor Flow, Seaborn, Scikit-learn, MLflow2+ years of experience with distributed…