Data Enthusiast

Collaborated with database engineers to implement ETL process, wrote and optimized SQL queries to perform data extraction and merging from SQL server database.Responsible for Data Cleaning, features scaling, features engineering by using NumPy and Pandas in Python. Performed Exploratory Data analysis (EDA) to maximize insight into the dataset, detect the outliers and extract important variables by graphically and Numerically.•Applied resampling methods like Synthetic Minority Over Sampling Technique (SMOTE) to balance the classes in large data sets. Implemented algorithms such as Principal Component Analysis (PCA) for dimensionality reduction and normalize the large datasets.• Implemented Deep learning model using YOLO algorithm to predict Realtime detection of anomalies in Steel Manufacturing and performed various hyperparameter tuning to increase the performance of the model • Developing a customised Deep Learning based OCR model to capture the right information from a document that needs to be processed and approved.

Performed Extraction, Transformation and Loading (ETL) of the financial data using Microsoft SSIS and IBM DataStage.Developed SQL stored procedures, views, indexes and complex SQL queries for extracting, manipulating and loading the customer and transaction data.Created visually impactful reports and dashboards for real time insights on key performance metrics using Tableau, SSRS and Excel (Pivot tables, Pivot charts).Built, maintained, and automated detailed models for city-level, regional, and global reporting with quality assurance as top priority