Optum Tech (UnitedHealth Group) is hiring a Principal Data Scientist to lead the design, development, and deployment of advanced machine-learning solutions. In this role, you will define the end-to-end ML architecture, select tools and frameworks, drive proof-of-concepts, and guide engineering teams in productionizing scalable AI services. You will provide technical guidance and mentorship to junior engineers without formal people management responsibilities, partnering closely with engineering, product, and cross-functional teams.
What You'll Do
- Lead solution architecture and hands-on development of machine learning and generative AI applications.
- Design, build, and deploy scalable, production-grade AI solutions using traditional ML, deep learning, and modern LLM-based approaches.
- Balance architectural leadership with hands-on execution across complex AI/ML initiatives.
- Provide technical guidance and mentorship to junior engineers through collaboration and code/design reviews.
- Partner closely with engineering, product, and cross-functional teams to deliver high-impact AI solutions aligned with enterprise standards.
- Design, develop, and deploy AI-powered solutions to address complex business challenges.
- Lead proof-of-concept experiments in generative AI (e.g., transformers, GANs, diffusion models) to solve business problems.
- Establish best practices for model governance, versioning, reproducibility, and security.
- Collaborate with data engineers, data scientists, software engineers, and product managers to translate business requirements into technical solutions.
- Evaluate emerging tools, libraries, and research to drive innovation and maintain competitive edge.
- Document architecture designs, conduct design reviews, and present technical proposals to stakeholders.
What We're Looking For
- 10+ years of experience designing, building, and deploying production machine learning solutions.
- Deep expertise in either NLP or Computer Vision, with multiple years of hands-on solution ownership in that domain.
- Deep expertise in core ML and statistical methods: supervised/unsupervised learning, regression, classification, clustering, time series, Bayesian modeling.
- Proven solid foundation in traditional ML and deep learning, demonstrated through substantive work prior to or alongside recent GenAI efforts.
- Demonstrated experience with cloud ML services and infrastructure design on at least one major cloud platform (AWS, Azure, or GCP).
- Recent experience (approximately last three years) building GenAI applications using LLMs and frameworks such as LangChain and/or LangGraph.
- Hands-on programming experience in Python and ML frameworks (e.g., PyTorch, TensorFlow).
- Demonstrated familiarity with big data technologies: Apache Spark, Hadoop, Dask.
- Ability to define cloud-native ML infrastructure on Azure, AWS, or GCP: containerization (Docker/Kubernetes), ML pipelines (SageMaker, Vertex AI, Azure ML), MLOps (CI/CD, model registry, monitoring).
- Proficiency in deep learning frameworks: TensorFlow, Keras, PyTorch.
- Practical experience building or fine-tuning generative models (e.g., GPT, BERT, Stable Diffusion, custom architectures).
- Proven solid background in probability, linear algebra, and statistical inference.
- Demonstrated track record of moving models from research/POC into production at scale.
- Proven excellent problem-solving ability and solid verbal/written communication skills.
Nice to Have
- Experience working with healthcare data, systems, or use cases.
- Experience with MLOps tools: MLflow, Kubeflow, TFX, Airflow or equivalent.
- Proven knowledge of data visualization tools (Tableau, Power BI) and dashboarding.
- Work supporting U.S.-based healthcare or enterprise environments.
- Reside in Minnesota.
Technical Stack
- Languages & Core Frameworks: Python, PyTorch, TensorFlow, Keras, LangChain, LangGraph
- Big Data & Compute: Apache Spark, Hadoop, Dask
- Infrastructure & Cloud: Docker, Kubernetes, AWS, Azure, GCP
- ML Platforms & MLOps: SageMaker, Vertex AI, Azure ML, MLflow, Kubeflow, TFX, Airflow
- Visualization: Tableau, Power BI
Team & Environment
You will partner with engineering, product, and cross-functional teams. You will provide technical guidance and mentorship to junior engineers.
Benefits & Compensation
- Compensation range: $112,700 to $193,200 annually.
- Comprehensive benefits package.
- Incentive and recognition programs.
- Equity stock purchase.
- 401k contribution.
Work Mode
This role is hybrid. Locations are within the United States.
Our culture is Caring. Connecting. Growing together. Our mission is to help people live healthier lives and make the health system work better for everyone. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes.
UnitedHealth Group is 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.
