Jaya Mundre

Data Analyst with experience in SQL, Python, and data visualization, focused on building dashboards, improving data accuracy, and supporting business decision-making. Skilled in working with large datasets, identifying patterns, and delivering insights in fast-paced environments. Seeking entry-level Data Analyst or Financial Analyst roles.

Financial Analyst at State Street (2025-06 – Present)

• Used SQL (Oracle, SQL Server) to extract and validate transaction, holdings, and cash data, improving reporting accuracy by ~30%
• Built Tableau and Power BI dashboards to track portfolio exposure, NAV movement, and operational KPIs, reducing manual reporting effort by ~40%
• Integrated Bloomberg and Refinitiv data with internal datasets to support valuation checks and trend analysis
• Applied Python (scikit-learn) models to identify transaction anomalies, improving early risk detection by ~25%
• Collaborated with cross-functional teams (risk, compliance, engineering) to support reporting, audit, and data preparation in an Agile.

FRAUD DATA ANALYST at TaskUs (2022-02 – 2023-09)

• Supported DoorDash's fraud verification campaign by analyzing high-volume transactional datasets, helping reduce fraudulent activity on customer profiles by 80% through targeted identification and predictive modeling.
• Evaluated large datasets to identify trends, patterns, and correlations for business insights.
• Created predictive models to forecast fraudulent behavior patterns, increasing fraud detection accuracy by approximately 30% and reducing manual review time by 40%, improving overall fraud resolution efficiency.
• Applied agile practices to ensure iterative improvements and maintained clear documentation to support audits and compliance reviews.

QUALITY ANALYST at Teleperformance (2020-08 – 2022-02)

• Conducted detailed call quality audits with an accuracy rate exceeding 95%, ensuring strict adherence to service standards and contributing to enhanced customer experience.
• Collaborated with cross-functional teams to gather reporting requirements, enabling tailored dashboards that supported leadership decision-making and operational planning.
• Designed and delivered Power BI dashboards tracking call center KPIs and performance metrics, improving reporting efficiency by 25% through performance tuning and query optimization.
• Assessed call center operational data using SQL and Python to identify inefficiencies, resulting in a 20% improvement in forecasting accuracy and enhanced decision-making across teams.

Master of Science in Analytics – Northeastern University (2023-09 – 2025-07)