Senior Manager, Data Science - Remote

UnitedHealth Group•Minnetonka, MN

4d•$112,700 - $193,200•Remote

About The Position

The Experience Analytics and Reporting (EAR) team is seeking an analytically driven Senior Manager, Data Science to lead horizontal AI, analytics, and reporting initiatives that span all CCT workstreams as part of the enterprise Contact Center Transformation effort. This role is ideal for a hands-on data science leader who thrives in fast-paced, high-stakes environments and is passionate about improving the member and advocate experience through AI. The key focus of the role is to drive AI model development and optimization, own cross-workstream performance measurement and reporting, and identify and quantify new opportunities to reduce contacts, improve self-service adoption, and increase advocate efficiency across UHC and Optum.

Requirements

3+ years of experience in data science, advanced analytics, or applied machine learning
3+ years of experience using data and models to create strategic solutions to business opportunities
2+ years of experience leading analytics or data science initiatives across multiple concurrent projects
2+ years of experience with AI/ML solutions in a production or operational environment
2+ years of experience working across cloud data platforms (e.g., Azure, Google Cloud)
2+ years of healthcare experience
2+ years of experience in highly collaborative roles within a highly matrixed environment
1+ years of experience conducting business and financial analyses (opportunity sizing, cost/benefit)

Nice To Haves

Proven understanding of contact center operations and advocate-facing AI tooling
Experience with AI governance processes, including AI Review Board (AIRB) preparation and approvals
Experience influencing outcomes of others who are not direct reports
Demonstrated curiosity, adaptability, and ability to work with changing direction and priorities
Proven technical fluency across data pipelines, model performance measurement, and BI/reporting tools

Responsibilities

Lead AI model development, optimization, and performance measurement across multiple CCT workstreams
Define and maintain measurement frameworks, KPI definitions, and value-realization methodologies for AI-driven initiatives
Partner with workstream owners and solution development teams to evaluate model performance, prioritize enhancements, and improve accuracy, coverage, adoption, and business impact
Diagnose issues across multiple data pipelines and cloud stacks (Azure and Google Cloud) and drive root-cause analysis when AI tools underperform
Facilitate collaboration across business, operations, product, and technology teams to ensure cohesive, consistent analytics across workstreams
Serve as a central point of contact for AI performance reporting, opportunity identification, and data-driven decision support
Influence stakeholders at all levels, fostering solid relationships to scale successful AI capabilities across the enterprise
Identify emerging risks, model degradation, or pipeline gaps and drive solutions proactively
Use data and model-level insights to diagnose root causes and guide prioritization and investment decisions
Recommend scalable improvements that advance model performance and operational consistency
Drive horizontal CCT AI and analytics activities, including but not limited to: Advocate-facing AI product performance and adoption analytics, Cross-workstream opportunity identification and sizing, AI model measurement, optimization, and value realization tracking, Algorithm maintenance and AI Review Board (AIRB) preparation, submission, and approvals
Prepare and present executive-level summaries, dashboards, status reports, and business cases for AI initiatives
Synthesize complex model and analytics details into clear, actionable information for leadership audiences
Ensure stakeholders are continuously informed on model performance, adoption, risks, and realized value
Partner with operations, training, and change management teams to ensure smooth adoption of AI tools and workflows
Track and measure outcomes, ensuring benefits realization and performance alignment across workstreams
Support continuous improvement through retrospective reviews and lessons learned
Ensures all impacted workstreams and AI products are identified and engaged
Ensures all model, data, and pipeline dependencies/linkages are identified
Obtains agreement on analytics and measurement scope from stakeholders
Ensures all reporting deliverables and success criteria are defined
Develops and maintains measurement frameworks, model documentation, and AIRB submissions
Provides regular performance, adoption, and value-realization communications to stakeholders
Oversees opportunity sizing and cost/benefit analysis, ensuring thorough evaluation and obtaining necessary approvals