S
Sai Aravind Donga
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Indianapolis, Indiana, United States
Résumé
Jobs
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Data AnalystPlaidOct 2024 - Current (2 years 1 month)• Worked on Customer Transaction Analysis to Improve Product Personalization collaborating with Product Engineering and Data Science teams in agile sprints and requirement sessions to align analysis with business objectives. • Wrote optimized SQL queries using window functions and CTEs on AWS Athena querying structured JSON transaction data reducing query runtime by 40% and managed ETL pipelines with AWS Glue for seamless data ingestion and transformation. • Performed cohort and trend analysis on anonymized transactions to segment users by spending patterns improving segmentation accuracy by 25% enabling more effective product personalization and marketing targeting. • Leveraged Python pandas NumPy and SciPy for statistical hypothesis t- Data AnalystHSBCJan 2021 - Jul 2023 (2 years 7 months)• Gathered and integrated loan and customer credit data from Oracle and Hadoop using Azure Data Factory in agile collaboration with credit risk and IT teams. Conducted requirement sessions to align on default prediction objectives and KPIs. • Extracted transformed and optimized large datasets via SQL Server and Azure Data Lake ETL pipelines reducing query time by 30% and ensuring high-quality up-to-date data for credit risk modeling and operational reporting. • Performed exploratory data analysis using Python Pandas and NumPy to identify critical default predictors enhancing feature engineering and improving predictive model performance by 20% through detailed statistical insights and data visualization. • Built and validated logistic r
- Jr. Data AnalystHSBCJan 2020 - Dec 2020 (1 year)• Utilized SQL to extract and preprocess customer account, transaction, and service usage data from HSBC's data warehouse, ensuring data quality and consistency for comprehensive churn analysis across multiple customer segments. • Conducted exploratory data analysis (EDA) using Python (Pandas, Matplotlib, Seaborn) to identify key behavioral patterns and features correlated with customer attrition, supporting feature engineering for churn prediction models. • Developed and visualized churn prediction dashboards with Tableau, presenting actionable insights to stakeholders for customer retention strategies, while continuously monitoring model performance and updating datasets to improve predictive accuracy.
Education
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- Master of ScienceIndiana University IndianapolisAug 2023 - May 2025 (1 year 10 months)
- Bachelor of TechnologyLovely Professional UniversityAug 2016 - May 2020 (3 years 10 months)