Rashmi Thakre

UBS for HR – ADA Analytics
• Successfully led the migration of data from Oracle database to Azure environment,
ensuring minimal downtime and maximum data integrity.
• Designed and implemented data migration strategies, including schema mapping,
data transformation, and validation processes, automated the manual data
reconciliation process between the different increasing the data accuracy and
efficiency by 90%
• Developed and executed test cases to validate data migration processes, ensuring
data completeness, accuracy, and consistency.
• Implemented monitoring and logging mechanisms to track data migration progress
and troubleshoot issues.
• Used Scala to store streaming data to HDFS and to implement Spark for faster
processing of data (40% faster)

HSBC for Global Liquidity and Cash Management
• Worked on Core Banking Project for HSBC for Global Liquidity and Cash
Management, Bangalore.
• Have done Data cleaning and missing value handling for the customer raw data using
Python
• Visualizing customer transactions data using Tableau and providing recommendations
to the business team.
• Developed powerful insights based on EDA, Entity resolution and creating data
pipelines for projects increasing the customer retention and customer transactions
consequently for about 20-30%.
• Expert at Analyzing, Designing, and Re-engineering systems applications and
business processes.
• Led Daily Standups, Retrospective meetings, Story grooming, and Iteration planning
meetings

MetLife US- Identifying Outlier Claims

• To identify claims that unexpectedly become high-cost losses by using historical
reviews available from previous claims for similarities and send alerts to claims
specialist to minimize any similar future events.

Wells Fargo- Expense requirements analysis Technology

• To develop a clear set of critical success factors that turn short-term expense
reduction into long-term, sustainable changes and ideal expense management.
Identifying the roadblocks associated with Financial and management reporting.
• Utilized SQL queries to extract and analyze data from relational databases, resulting
in increased efficiency in data retrieval.