• Collect, clean, process, and analyze potential and current clients’ pharmaceutical data – using SQL, R, Python, and MS Excel as appropriate – to support the Underwriting and Sales teams in the acquisition of new business and retention of current clients • Thoroughly understand internal and external data fields, identify patterns of data irregularities, and improve data quality and intake • Reach out to and question relevant parties regarding any data ambiguity and request any additional data elements that may be required or beneficial for analysis • Assist in the writing and maintenance of the Underwriting infrastructure code in SQL, R, and Python • Participate in process enhancement for data analytics and reporting • Provide ad-hoc analytics support to the Underwriting team in the successful completion of all bid opportunities • Provide analytics support to the Pricing, Clinical Account Management, and Implementation teams to facilitate client transitions as needed • Responsible for adherence to the Capital Rx Code of Conduct, including reporting of noncompliance.

• Own the tracking, reporting, and analysis of Client Services activities • lead the development and automation of regular insights that move the needle on customer health and retention • Write, optimize, and execute complex SQL queries • responsible for manipulating customer and business data from across our tech stack to uncover hidden trends • Act as a data consultant for cross-functional partners • translate non-technical business requirements into customized technical queries and dashboards • Operate effectively within a global team, ensuring seamless asynchronous collaboration and high-quality hand-offs with US-based partners across a 12-hour time difference • Proactively assist in maintaining and optimizing our data infrastructure (BigQuery/Looker) • identify and fix pipeline or logic gaps before they impact stakeholders • Develop repeatable frameworks and automated processes to handle common analysis requests, increasing team efficiency and reducing manual toil • Regularly audit data outputs for anomalies and uphold the 'Gold Standard' of data quality

• Help support coordinated, client-centered care by turning data into meaningful support for teams improving access to care in rural communities. • Schedule: Monday-Friday, starting early around 6:30 am. • Plays an important role in supporting high-quality, client-centered care within the Health Home program through accurate data management, strong communication, and reliable coordination across teams. • Helps ensure care teams have timely, organized information needed to support individuals receiving services. • Maintains healthcare tracking systems, validates data, and generates reports contributing to program effectiveness, operational efficiency, and compliance. • Support special projects, operational improvements, and department initiatives. • Participate in required meetings, trainings, and organizational events. • Perform additional duties as assigned by department leadership.

• Will be responsible for applying mathematical and statistical techniques and/or innovative /quantitative analytical approaches to draw conclusions and make 'insight to action' recommendations to answer business objectives and drive change. • Collaborate with Quality Improvement teams to define metrics and develop data-driven solutions that support clinical and operational QI initiatives. • Analyze large datasets to identify trends, patterns, and opportunities for improving patient outcomes, reducing costs, and enhancing service delivery. • Assists with strategic intelligence development through report writing, dashboard development, and front-end scripting, using a variety of platforms including PowerBI, SQL, and Excel. • Design, develop, and maintain dashboards and reports to monitor key performance indicators (KPIs) related to quality improvement goals. • Translate complex data into actionable insights for both technical and non-technical stakeholders through visualizations, presentations, and written reports • Utilize statistical methods and modeling techniques to support evidence-based decision-making. • Integrate different data sources, creating one unified, manipulable data source. • Work with internal departments and external partners to acquire, validate, and integrate data for analysis. • Maintains up-to-date knowledge by reading technical journals, and attending seminars, internal user groups, and workshops to learn about new developments and changing technology trends. • Stay current with healthcare regulations, quality measurement standards (e.g., HEDIS, NCQA, CMS), and industry best practices. • Collaborates with other departments in a mentoring and guidance role on the data tools available.