Optum Tech is a global leader in health care innovation. Our teams develop cutting-edge solutions that help people live healthier lives and help make the health system work better for everyone. From advanced data analytics and AI to cybersecurity, we use innovative approaches to solve some of health care's most complex challenges. Your contributions here have the potential to change lives. Ready to build the next breakthrough? Join us to start Caring. Connecting. Growing together.
We are seeking a seasoned Principal Data Scientist to lead design, development and deployment of advanced machine-learning solutions. In this role you will define end-to-end ML architecture, select appropriate tools and frameworks, drive POCs and guide engineering teams in productionizing scalable AI services. A solid foundation in statistics, deep learning and generative AI, hands-on cloud expertise, and exceptional communication skills are essential. The Principal Data Scientist designs and builds production grade ML and GenAI solutions, while providing technical guidance and mentorship to junior engineers without formal people management responsibilities.
You'll enjoy the flexibility to work remotely* from anywhere within the U.S., preferably in Minnesota, as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.
Primary Responsibilities:
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 (no people management)
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 (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
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:
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 (GenAI only backgrounds without prior ML depth are not sufficient)
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
Preferred Qualifications:
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
*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy.
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 $112,700 to $193,200 annually based on full-time employment. We comply with all minimum wage laws as applicable.
Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.
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.
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.
UnitedHealth Group is a drug - free workplace. Candidates are required to pass a drug test before beginning employment.
