Data Scientist, Applied Analytics and Production Solutions (Remote)

UnitedHealth Group•Eden Prairie, MN

12d•$72,800 - $130,000•Remote

About The Position

Optum's Enterprise Clinical Services team is seeking a Data Scientist to support the implementation, execution, and expansion of a growing portfolio of applied analytics, automation, AI, and operational solutions that improve healthcare delivery and operational efficiency. This role helps ensure that production models, automations, data pipelines, reporting solutions, optimization tools, and decision-support assets remain reliable, supported, documented, and continuously improved. Working at the intersection of data science, engineering, and operations, you will own day-to-day execution and support for assigned production capabilities while contributing to new solution development. The role is well suited to someone who can quickly learn new datasets, systems, business domains, and analytical methods, and who wants to grow toward broader solution ownership. 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

2+ years of post college experience
2+ years of experience in data analytics using Python
2+ years of experience designing, implementing, and maintaining automated processes or workflows
2+ years of experience creating data visualizations, dashboards, or business intelligence solutions using Power BI, Tableau, or similar tools
2+ years of experience with SQL, data engineering, data modeling, query optimization, or database development using Microsoft SQL Server or a similar platform
1+ years of experience applying analytical, statistical, optimization, or machine learning techniques to business problems
Working knowledge of predictive modeling, machine learning, artificial intelligence, natural language processing, and their business applications
Proven solid analytical, problem-solving, written, and verbal communication skills
Proven ability to work independently in environments with ambiguity, incomplete documentation, and evolving requirements, and to learn new technologies and business domains quickly

Nice To Haves

Experience supporting production analytical systems, models, data pipelines, or automation solutions
Experience in healthcare analytics or healthcare operations
Experience in call-center or contact-center operations
Experience in logistics, operations research, supply chain, workforce optimization, scheduling, routing, network optimization, or Geographic Information Systems (GIS)
Experience with Generative AI, large language models (LLMs), natural language processing (NLP), voice analytics, or AI-enabled quality assurance
Experience administering analytics infrastructure, including compute resources, databases, job-scheduling platforms, and application environments used for data science or business intelligence solutions

Responsibilities

Monitor and support production models, automations, decision-support tools, data pipelines, and reporting assets
Troubleshoot production issues, coordinate resolution activities, and serve as a primary support contact for assigned capabilities
Evaluate solution and model performance, investigate operational issues, identify root causes, and recommend improvements
Maintain technical documentation, operational runbooks, monitoring guidance, and knowledge-sharing resources
Support production reporting, validation, operational readiness, and continuous improvement activities
Partner with senior data scientists and business leaders to operationalize research, pilot emerging capabilities, and transition solutions into production environments
Develop and maintain scalable data pipelines, automated workflows, analytical processes, and application components
Create dashboards and operational reports that translate complex analytics and model results for non-technical stakeholders
Conduct ad hoc analyses supporting strategic and operational initiatives
Support the design, testing, validation, and deployment of analytical and AI-enabled capabilities
Perform peer reviews of code, analytical methods, and technical processes, and contribute reusable frameworks and best practices
Build expertise across multiple portfolios, systems, and business domains
Participate in cross-training, documentation, and knowledge-transfer activities that reduce concentrated ownership
Expand ownership of analytical and technical initiatives as portfolio and business knowledge grows
Communicate technical concepts, findings, risks, and recommendations clearly to technical and non-technical partners