Data Analyst at Exact Medicare

Westerville, Ohio, United States -

Full Time

Start Date

Immediate

Expiry Date

04 Feb, 26

Salary

0.0

Posted On

06 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analysis, SQL, ETL, Power BI, Python, Data Visualization, Data Pipelines, Data Accuracy, Collaboration, Problem Solving, Attention to Detail, Documentation, Cloud Computing, Business Analytics, Insurance Industry Knowledge, Trend Analysis

Industry

Insurance Agencies and Brokerages

Description

Position Overview We’re seeking a Data Analyst to join our growing Data Analytics and Reporting team. This newly created role will support key 2026 data initiatives, including enhanced reporting on commission audits, B2B setup, and other strategic data projects. The ideal candidate will be skilled at designing and implementing data-driven solutions that support decision-making across the organization. You’ll play a critical role in building and maintaining data pipelines, developing automated reporting, and uncovering insights that drive process improvements. This position offers the opportunity to help shape new analytics frameworks and optimize existing systems during an exciting phase of data transformation. Key Responsibilities Design, develop, and implement data pipelines for processing and analyzing Medicare insurance commissions data, ensuring data accuracy and efficiency. Work closely with Sales, Finance, and Commissions teams to understand business requirements and deliver data solutions that meet those needs. Develop and automate ETL (Extract, Transform, Load) processes to ensure seamless data integration from multiple sources (e.g., CRM systems, billing systems, spreadsheets). Conduct data analysis to identify trends, discrepancies, or issues related to payouts, calculations, and performance metrics. Build and maintain Power BI dashboards and reports to visualize metrics, performance, and trends. Provide actionable insights and recommendations for improving data processes, identifying areas for optimization, and aligning with business goals. Collaborate with cross-functional teams to ensure data consistency, accuracy, and compliance. Perform ad hoc analyses to address business queries and provide insights into commission-related patterns. Create and maintain documentation for all data processes, models, and systems used. Skills and Qualifications Bachelor’s degree in Data Science, Computer Science, Business Analytics, or a related field. 2+ years of experience as a Data Analyst , preferably within the insurance industry or a Medicare-related environment. Proficiency in SQL and database management (e.g., MySQL, PostgreSQL, or similar). Experience with ETL processes and managing large, complex datasets. Strong proficiency in Power BI or other visualization tools. Experience with Python (or R) for data analysis, automation, and process optimization. Familiarity with cloud-based data environments such as AWS, Azure, or Google Cloud. Excellent analytical and problem-solving skills with strong attention to detail. Strong communication skills, with the ability to translate complex data insights into clear, actionable business recommendations. Demonstrated ability to work collaboratively across departments to support evolving data needs. Work Environment This is a full-time, hybrid position, offering flexibility to work remotely while maintaining regular collaboration with in-office team members. About the Role This is an exciting opportunity for an analytical thinker who thrives in a dynamic environment. You’ll contribute directly to shaping how our organization captures, processes, and leverages data to drive success. As we continue to enhance and integrate new systems, your work will help streamline reporting processes and ensure our teams have the insights they need to make informed decisions.

Responsibilities

The Data Analyst will design, develop, and implement data pipelines for processing Medicare insurance commissions data and automate reporting processes. This role involves collaborating with various teams to deliver data solutions that support business needs and drive process improvements.