Senior Data Scientist

UnitedHealth Group•Eden Prairie, MN

13d•$91,700 - $163,700•Remote

About The Position

Optum Insight is partnering with payers, providers, governments, and life sciences companies to simplify and enhance clinical, administrative, and financial processes through software-enabled services and analytics, while advancing value-based care as part of Optum's broader mission to help millions of people live healthier lives. Through this work, teams contribute to better health outcomes by improving how care, data, and services connect across the health system. Join us to start Caring. Connecting. Growing together. You’ll enjoy the flexibility to work remotely from anywhere within the U.S. 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 for a minimum of four days per week. The Clinical Decision Support (CDS) Engineering team, a unit within the Optum Insight Technology organization, is responsible for building commercial products that help payers and providers with administrative- and clinician-focused CDS solutions. In this role as a Principal Data Scientist, you will lead high-impact AI initiatives characterized by scale and complexity. You will architect robust, secure AI systems, train state-of-the-art transformer and multimodal models, and bridge the gap between AI research and production software engineering. By extracting deep insights from healthcare data and maintaining the highest standards of responsible and ethical AI, you will help shape the next generation of intelligent health solutions.

Requirements

Master’s / PHD degree in Math, Applied Math, Statistics, Computer Science, Physics, Engineering or related field
5+ years of industry or academic experience in machine learning or a related data science field
5+ years of experience building machine learning models
5+ years of experience with Python programming and deep learning frameworks (e.g., PyTorch or TensorFlow)

Nice To Haves

Experience working with complex structured and non-structured datasets
Practical experience with public cloud AI technology stacks and modern data ecosystems
Understanding of statistics and statistical best practices
Experience applying Generative AI, Large Language Models (LLMs) to business problem
Experience with state-of-the-art ML architectures (e.g., Transformers/LLMs, multimodal modeling)

Responsibilities

Drive end-to-end generative AI and machine learning projects that have a high degree of ambiguity, scale, and complexity
Design robust AI architectures, ensuring that systems are scalable, secure, and efficient; select appropriate technologies, frameworks, and methodologies
Develop predictive, prescriptive, and optimization models to improve business performance and operational effectiveness using machine learning, deep learning, NLP, and generative AI capabilities
Formulate hypotheses, conduct experiments, and validate findings using rigorous analytical and statistical methodologies
Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement
Partner with business, product, operations, and technology teams to translate complex analytical findings into clear business recommendations and executive-level insights
Perform hands-on analysis and modeling of healthcare data sets to develop insights that increase business value
Run A/B experiments, gather data, and perform statistical analysis; continuously assess AI system performance and optimize algorithms and models to improve accuracy and efficiency
Research and implement innovative machine learning approaches, evaluate emerging trends to inform solution design, and translate cutting-edge AI advancements into production-ready capabilities that can be re-used across the enterprise
Uphold ethical AI principles by embedding fairness, transparency, and accountability throughout the model development lifecycle