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Sr. Data Analyst
SmartLight AnalyticsUnited Statesfull_timeVerifiedPosted 20 Jan 2026
About the role
Job Summary:
In this role, you will develop analytical insights to identify payment anomalies in client’s healthcare claims data. To be successful in the role, you will have sound knowledge and experience with Statistical Models, Data Mining, and building dashboards to deliver insights, insights communication and presentation, as well as demonstrating the ability to combine advanced analytics skills with exceptional business acumen. The Data Analyst II will collaborate with cross-functional teams to translate complex data findings into clear, concise, and actionable recommendations.
This position is only eligible for legal residents of the United States of America.
This position is a remote position.
Key Responsibilities:
Data Analysis and Interpretation:
In this role, you will develop analytical insights to identify payment anomalies in client’s healthcare claims data. To be successful in the role, you will have sound knowledge and experience with Statistical Models, Data Mining, and building dashboards to deliver insights, insights communication and presentation, as well as demonstrating the ability to combine advanced analytics skills with exceptional business acumen. The Data Analyst II will collaborate with cross-functional teams to translate complex data findings into clear, concise, and actionable recommendations.
This position is only eligible for legal residents of the United States of America.
This position is a remote position.
Key Responsibilities:
Data Analysis and Interpretation:
- Develop a deep understanding of the key initiative of the organization and be able to provide analytical solutions that provides actionable recommendations to drive the success of the key initiatives.
- On-going monitoring of product lines including but not limited to the success metrics for each model and dashboards required for executive decision-making.
- Collect, clean, and analyze data from multiple sources to identify trends, patterns, and insights.
- Apply statistical methods and advanced analytical techniques to solve business challenges and provide forecasts or predictive models.
- Monitor data integrity by conducting regular audits and ensuring accuracy and completeness of datasets.
- Develop dashboards using claims and eligibility data with analytical insights to assist in executive decision making.
- Work with business stakeholders to understand their goals, challenges, and opportunities, and translate their needs into analytical projects.
- Prepare on-demand analyses and ad-hoc reports and insights.
- Present findings to stakeholders and translate insights into strategic recommendations.
- Identify opportunities to automate data processes, streamline workflows, and improve reporting efficiency.
- Document analytical methodologies, data workflows, and insights to ensure transparency and knowledge sharing across the organization.
- Communicate analytical findings and recommendations in a clear and concise way to non-technical audiences, both in oral and written presentations.
- Work closely with Information Management teams to automate recurring tasks and improve processes to continually increase efficiency.
- Education:
- Bachelor’s degree in business, economics, finance, mathematics or related field.
- Experience:
- A minimum of five (5) years of analytical work experience with healthcare claims data
- Experience and understanding of data analysis and appropriate application of these capabilities in a business performance environment
- SQL: 5+ years (Required)
- Healthcare claims: 5+ years (Required)
Technical Skills:
- Proficiency in SQL and experience with data querying and database management.
- Experience with data visualization tools such as Tableau, Power BI, or QlikView.
- Familiarity with statistical software or programming languages (e.g., R, Python, SAS, or SPSS).
- Working knowledge of ETL processes and data pipelines
- Demonstrated ability to analyze data and synthesize findings into clear insights.
- Experience with statistical analysis, forecasting, regression models, and predict
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