Optum is a global health services and technology organization dedicated to making healthier lives possible. Our team's work directly enhances health outcomes by connecting individuals with essential care, pharmacy benefits, data, and resources. We foster an inclusive culture, offering opportunities to collaborate with talented peers, access comprehensive benefits, and pursue career development.

Join us in advancing health optimization worldwide and making a tangible impact on the communities we serve. Together, we will embrace a spirit of Caring, Connecting, and Growing.

Design, construct, and maintain robust data pipelines, analytical datasets, and reporting infrastructure to support customer experience, market research, and business performance insights.

Develop advanced analytical solutions, including statistical modeling, machine learning, forecasting, segmentation, and other techniques to address complex business inquiries.

Integrate diverse data sources such as surveys, behavioral data, operational metrics, digital interactions, and third-party information to create comprehensive customer, market, and business outcome views.

Leverage automation, AI, and modern analytics tools to enhance research operations, boost analytical efficiency, and generate actionable insights.

Collaborate closely with research, business, technology, and data governance teams to deliver dependable, scalable, and well-managed analytics solutions.

Clearly articulate findings, recommendations, and their business implications to both technical and non-technical audiences, including senior leadership.

A Bachelor's degree in a quantitative field such as Data Science, Statistics, Computer Science, Economics, Mathematics, Engineering, Business Analytics, or Market Research is required.

Possess at least 3 years of professional experience in data science, analytics engineering, data engineering, business intelligence, or advanced analytics.

Demonstrate strong programming proficiency in Python and SAS.

Exhibit experience in building analytics pipelines, data workflows, dashboards, statistical models, or machine learning solutions.

Familiarity with cloud or enterprise data platforms like Azure, Databricks, Snowflake, AWS, Google Cloud, or similar is essential.

Advanced SQL skills and proven experience working with large-scale structured and unstructured datasets are necessary.

Show a strong ability to translate business challenges into analytical approaches and effectively communicate insights to stakeholders.