Recent Engagement:Arthritis foundation - Facilitate elaboration sessions to understand the organization’s needs and objectives to gather accurate data requirements. Analyze existing data processes and workflows within the organization to identify areas of improvement and contribute to data migration design. Map the organization’s requirements to the features and functionalities of NPSP to ensure a fully realized and effective solution. Creation of different models for every step as part of the data migration strategy developed.

Deloitte supported the Lululemon to optimize and implement new features into Lululemon’s forecasting and replenishment engine. Collaborated with client to gather requirements, ensuring project alignment with customer needs and expectations. Successfully delivered Pride (name) project, consistently meeting scope, schedule, and budget requirements. Managed project teams of 9 members, fostering a collaborative environment and enabling cross-functional synergy. Exploration of different technologies to support and enhance ML model operations.

Data Engineer (Contingent Worker) in Meta from Deloitte.CASD (Cross-App Soft-Match) program to modify python pipelines and make adhoc changes according to the requirements. Conducting code reviews, delegating tasks to team members, understanding any blockers they have and unblocking them. Implemented new functionalities in the dashboards to view data according to the user requirement (Mostly presto sql scripts). Conducted dry-run tests to ensure full-proof execution of customized scripts before deployment in production environments. Reviewed the existing functionalities in the system for debugging, fixing and became the first go-to person to reach in case of any issue or queries

Applied analytical skills to extract, transform, and load raw input data into desired form. Worked on classification problem that required two big datasets (~1 million). Studied and modified different compression techniques to achieve high compression. Hands-on experience with machine learning models (Neural Networks and Decision Trees) using SK-Learn and TensorFlow libraries. Feature analysis, classification, cross-validation, and Hypothesis Testing. Hypothesis testing using paired t-test with 95% confidence level. Achieved similar accuracy values for compressed and uncompressed data. Best accuracy results for the model and approach were without compression (approximately 92.03%) and with compression (approximately 91.91%). Used Anaconda- Jupyter and Spyder, Python, Weka to address the tasks.

Effective recruitment brought down turnover from 95 to 65%.Inventory Management and cost reduction policies brought down food cost.Increase in sales by 30% increase in guest satisfaction.

Worked at client location for System Shyam Teleservices. Led a team of 17 individuals at offshore in producing a workable model to provide rewards-based tool. Increased sales by 27% using the reward program developed for client in a period of three years. Implemented ETL process code in Java, SAS, and Unix for SAS Data Integration. Data visualization using SAS Environment Manager. Possesses excellent skillset and experience in SAS Coding –Base SAS, SAS SQL, SAS EG, SAS DI Studio, SAS Macros, Stored Procedures, SAS Management Console. Strong experience in the design and development of SAS components and adept in writing, modifying SQL. Communicated with third-party clients and with consumer clients regarding troubleshooting bugs and issues. Used Eclipse, Vertica and Oracle DB, SQL, REST API and SAS.

The pivot from electronics engineer to software engineer. Started learning both core and advanced java while working for Citibank client. Designed and developed code across all layers of a JEE ap- plication. Support activities for RTView tool.Used Eclipse, Oracle DB, and RTView.

Key Responsibilities handled-(a) Vendor Vetting(b) KYC Client Screening(c) IPO Due Diligence(d) Comprehensive Due Diligence