Principal Data Scientist - Remote| Eden Prairie, Minnesota | Remote

Principal Data Scientist

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.

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.

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.

Primary 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
• Build machine learning models, perform proof-of-concept experiments, optimize and deploy models to production, and partner with software engineers to product ionize ML models
• 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
• Establish scalable, efficient, automated processes for large-scale data analysis, machine learning model development and validation, and MLOps
• 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
• Mentor and help recruit AI/ML scientists and machine learning engineers to the team

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 industry or academic experience in machine learning or a related data science field
• 5+ years of experience building machine learning models for business applications
• 5+ years of experience leading technical teams or complex AI/ML projects
• 4+ years of equivalent technical experience in software development/data science
• 3+ years of experience with Python programming and deep learning frameworks (e.g., PyTorch or Tensor Flow)
• 3+ years of experience with state-of-the-art ML architectures (e.g., Transformers/LLMs, multimodal modeling) and transformer fine-tuning

Preferred Qualifications:

• Experience working with complex healthcare datasets and clinical/claims analytics
• Practical experience with public cloud AI technology stacks, deployment, and MLOps methodologies (AWS preferred)
• Experience with big data processing tools such as Hadoop and Spark
• Experience with state-of-the-art ML algorithms and architectures (e.g., Transformers/LLMs, state space models such as Mamba, GNNs), legacy architecture maintenance/migration, and tradeoffs between…