Built and enhanced integrated datasets to support analyses of global sales trends, pricing, and customer engagement, improving data-driven decision-making across teams.Developed datasets incorporating key information like trade compliance details and automated credit control processes, reducing manual workload and ensuring seamless operations.Integrated customer segmentation data and key product attributes into internal tools, enabling targeted marketing strategies and deeper business insights.Automated credit management processes, including credit ratings and checks, ensuring operational stability and backup systems for critical workflows.Built comprehensive customer pricing datasets with historical discount data, enabling teams to track discounts and support audit requirements.Developed automated monthly reporting for pricing and sales performance, ensuring timely and consistent insights for pricing and operations teams.Delivered accurate datasets daily to various teams, ensuring quick access to critical data for agile decision-making across the organization.

Completed 62 IT requests, delivering diverse data solutions, including complex queries, ETL jobs, and optimizations using Oracle, HiveQL, and SQL for cross-divisional needs.Designed and implemented batch and micro-batch ETL pipelines to ensure reliable data flow for the product center, website, and risk supervision center.Led the migration of the data warehouse from Oracle to CDH, creating 210 ETL jobs, optimizing job streams, and reducing DayEndProcess runtime from 11 to 4 hours while cutting storage usage from 92% to 10%.Built 103 reusable data models for retail and wealth management, increasing reusability by 60% and supporting data-driven decision-making.Improved data quality, optimized job streams, and recommended enhancements for infrastructure and BI platforms.Developed data pipelines for investment performance and salary data ingestion in the new evaluation center.

Worked on knowledge graph in the field of investment banking

Description: Worked as a research intern at AIBRT, a research institute of psychology, under Dr. Robert Epstein.• Performed data cleaning, data analysis, data mining and data visualization of large, unorganized dataset with over 700,000 observations and 100+ features generated by an online survey of 10+ years using R and SPSS • Built a computational model of an abstractive theory that is essential to the research using R• Utilized external sources such as US census data to supplement missing information for the research paper • Developed insights from analyses and communicated with professor on using data-driven approaches to facilitate research process