Senior Data Analyst

• Managed end-to-end data workflows, including data extraction, transformation, and loading (ETL) processes, ensuring data accuracy and consistency.
• Conducted experiments with SQL indexing and filtering techniques, ultimately optimizing the SQL code, and realizing a 30% reduction in data access time on a database with tens of billions of rows of data.
• Created 3 population reports in PowerBI that provided valuable insights into demographics and user location enabling data-driven decision making for internal stakeholders. Reports were widely adopted by business clients and the sales department in determining marketing campaigns and customer retention strategies.
• Implemented advanced statistical techniques and predictive models in Python to perform predictive analysis on system error patterns. Developed an automated process using Pentaho Suite and Jenkins which monitored BSOD system counts and other critical KPIs in real-time. Automated system proactively alerted the IT team to any sudden spikes in system errors, enabling them to respond swiftly and reducing response time by 80%.
• Conducted in-depth research to understand and identify key pain points in the existing root cause analysis process. Developed a set of SQL templates that allowed for quick data extraction and transformation, automating the initial steps of data preparation, and eliminating the need for manual data manipulation. Integrated the SQL templates into Microsoft Excel and developed custom-designed dashboards in Tableau that visualized the results in a visually engaging and actionable format.

• Conducted rigorous testing and performance benchmarking to ensure the new data extraction process could handle large-scale data requests without compromising efficiency or data accuracy. Streamlined the process to handle the high-volume queries, thus reducing time spent on data requests by 75%.
• Developed a data request intake process to manage and fulfill a high volume of requests. Utilized OTRS ticket tracking to track and prioritize data requests, while allowed for timely written and verbal report preparation for Medicaid administrators, government officials, and other stakeholders.
• Collaborated closely with management and other cross-functional teams to design and implement a robust report review process, that outlined best practices for data collection, analysis, visualization, and documentation aimed at enhancing quality assurance (QA) for all reports generated within the organization.
• Collaborated with hospital administrators and healthcare providers to identify specific service challenges and pain points related to Medicaid claims data. Utilized advanced data analytics tools, including SQL, Python, and R, to perform comprehensive analyses of claims data. These analyses helped identify patterns, trends, and anomalies and facilitated decision making related to interventions and process improvements.
• Developed a comprehensive set of SQL code templates on a Vertica server, to assist in data retrieval for complex and specialized data queries not directly available through existing data tools. These templates produced consistent reports and ran complicated queries for coworkers reducing the need to rebuild queries and speeding up reporting by 50%.
• Collaborated as a key member of a multidisciplinary team on a large-scale trend analysis of chronic health conditions within the Medicaid population. Leveraged Cognos report templates to uncover valuable insights and opportunities for enhancing overall health outcomes and utilized advanced data visualization techniques within Cognos to create interactive and intuitive reports. Presented trends and patterns related to chronic health conditions that provided healthcare professionals and policymakers with actionable information and guided strategic interventions and healthcare policies.