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.
