Sr Principal Data Scientist - Remote

UnitedHealth Group•Minnetonka, MN

1d•$134,600 - $230,800•Remote

About The Position

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 highly accomplished and innovative Senior Principal Data Scientist to provide technical and analytical leadership for a strategic enterprise program focused on transforming complex business processes through advanced analytics, Artificial Intelligence (AI), and Machine Learning (ML). In this role, you will serve as a senior technical authority and strategic thought partner, applying deep expertise in data science, AI/ML, statistical modeling, experimentation, and decision science to solve high-impact enterprise challenges. Operating in ambiguity, you will frame complex and undefined problems, define new analytical approaches, and translate complex data into actionable insights and scalable AI-driven solutions that generate measurable business value. You will also shape the organization's advanced analytics and AI capabilities by establishing analytical standards, advancing innovative methodologies (including Generative AI, Large Language Models, and agentic capabilities), and mentoring data science talent across the enterprise. 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 a minimum of four days per week.

Requirements

Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or another quantitative discipline, or equivalent experience (e.g., 4+ additional years of quantitative analysis experience in lieu of degree)
10+ years of progressive experience in Data Science, Advanced Analytics, Machine Learning, AI, Operations Research, or related quantitative disciplines leading complex analytical initiatives
5+ years of experience with Python, R, SQL, or comparable programming languages for statistical modeling and data manipulation
5+ years of experience working with machine learning frameworks and ecosystems (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost)
3+ years of experience framing ambiguous business challenges, conducting hypothesis testing, experimental design, causal inference, and model validation on large-scale datasets
3+ years of experience providing technical leadership, mentoring data scientists, and establishing modeling standards
3+ years of experience translating technical analytics into executive-level narratives to influence business and investment decisions

Nice To Haves

Master's degree or PhD in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, Operations Research, or related quantitative discipline
Advanced expertise applying Generative AI, Large Language Models (LLMs), Agentic AI, NLP, or emerging AI technologies to enterprise business problems
Experience architecting and operationalizing AI-enabled decision intelligence solutions, recommendation systems, anomaly detection, or forecasting systems at scale
Experience with cloud-based analytics and AI platforms (e.g., AWS, Azure, GCP) and modern enterprise data ecosystems
Experience establishing model governance, explainability, monitoring, and lifecycle management (MLOps) in complex or highly regulated enterprise environments
Demonstrated track record of developing reusable analytical platforms, frameworks, accelerators, or intellectual property across enterprise functions

Responsibilities

Design, develop, and deploy AI-powered solutions to address complex business challenges with an emphasis on responsible use of AI, collaborating across research, engineering, and product teams to translate cutting-edge AI advancements into scalable, reusable enterprise capabilities
Serve as a senior technical leader and subject matter expert for enterprise data science, advanced analytics, AI, and machine learning initiatives across multidisciplinary teams
Lead analytical strategy for highly complex enterprise challenges, analyzing large-scale datasets to uncover hidden patterns, emerging trends, anomalies, and previously unexploited business opportunities
Develop predictive, prescriptive, causal, optimization, and decision intelligence solutions, applying advanced statistical methods, machine learning, Generative AI, and agentic AI capabilities
Frame ambiguous business challenges into testable hypotheses, lead rigorous experimentation and model validation, and deliver executive-level recommendations that influence strategic decision-making
Uphold ethical AI principles by embedding fairness, transparency, and accountability throughout the model development lifecycle
Use enterprise-approved AI tools to streamline workflows, automate tasks, evaluate emerging trends, and drive continuous improvement
Establish best practices for model development, explainability, monitoring, reproducibility, and responsible AI while mentoring data science talent across the organization