Sunith Kumar Samudrala

• 4 years 6 months; 4 years in HSBC Analytics.

Roles and Responsibilities: -

• End to End ETL processing from diverse databases and resulting in creation of Reports and Dashboards.
• Using SQL, SAS, and Python for Collecting and analyze data for multiple ad-hoc projects.
• Consistently worked with various teams like Fraud, Finance, Collections, Campaigns, and Business management team which is residing at onshore.
• Built data Analytics architecture for the data having HSBC products like Savings, Mortgages, mutual funds and insurances, majorly MasterCard Credit card etc., Which are then used to track, aggregate and analyze their sales then feed the results to business users.
• Standards for data transformation/processing are implemented on the projects to avoid redundancy and remove unwanted fields.

Accomplishments/Duties : -

• Collecting, reporting, and analyzing data in financial industry - plan, create, and maintain large scale data architectures to achieve Business goals and work on the requirements.
• Automated more than 120 reports (Coding, Formatting, QC, Delivering, and operational Trend Analysis) for various business teams.
• Saved ~10hrs of daily execution time to the Sales, Performance reports by creating intermediate tables, limiting columns in tables, and optimizing the code.
• Established QC framework on the data flowing from upstream sources to downstream and then the reporting layer.
• For all the enhancements made on the existing projects and new projects, final reports are delivered to user only after the QC is met and this QC is made by comparing the results of previous runs like for weekly report, Ex: trend QC for WOW (Week over Week) is created until for past 3 months and involves other statistical functions for analysis where the standards are derived from business to ensure the output values are aligned within it, same applies for MOM (month over month) and daily.
• Establishing and administrating the accesses for database level roles in SQL Server, worked mostly where the data analytics domain is involved.

• Analysis made on real time Apache logs of the travel company servers having the raw data which is converted in to structured data then the ELK (Elasticsearch Logstach and Kibana) is used for making instant visualization reports and in parallel real time data is processed continuously by using kafka, spark streaming and finally stored in Hadoop, small queries can done by using Hive on top of Hadoop.