Data Analyst Resume Example

• Involved in ETL process and database management, data mining, data cleaning,manipulating and storing data in database.
• Developing ad-hoc reports using SQL, SSRS, Tableau to find the trends on different data sets and presenting the insights to the Team.
• Extracted, interpreted and analyzed data to identify key metrics and transform raw data into meaningful, actionable information.
• Responsible for moderating the Intel AI community forum.
• Prepared Excels to keep a track of the tickets that the Community forum would get every week and used calculations to draw conclusions on SLA's and the users feedback.
• Experienced in data manipulation using python and python libraries such as pandas,Numpy,Scipy and Scikit-learn for data analysis and machine learning.
• Extracted Indian accident images from YouTube CCTV videos, processed images using LabelImg to get annotated files and implemented TensorFlow Object Detection API to detect accidents in images and identified the type of vehicle involved in an accident using Python and TensorFlow. Also used YOLO detection system to compare the accuracies .
• Implemented Diabetic Retinopathy use case using TensorFlow and got 83% of accuracy in Python.
• Worked on employees' data to predict the salary of a new employee with different features given using ML algorithms.
• Implemented bank notes classification used to classify the original notes and fraudulent notes which helps banks function appropriately using ML algorithms like Random Forest Classifier and Decision Tree and also applied Cross-validation Technique like K-fold to achieve better accuracy.
• Used machine learning and statistical modeling techniques to develop and evaluate algorithms to improve performance, quality, data management and accuracy.
• Developed Docker Images with Deep Learning frameworks (Tensorflow, Caffe, Pytorch, MxNet) for deploying in various systems. These Docker Images are performance optimized, compatibility tested and ready to deploy.
• Good Working knowledge in different Machine Learning algorithms like SVM, Random forest, Linear Regression, Logistic Regression, K Nearest Neighbors and so on.
• Performed Live object Detection on movidius Stick. Trained images using Tiny Yolo framework which produces graph file and the trained model( SSD mobileNet in caffe) along with labels.txt which includes list of labels. This graph file is sent to the movidius NCSDK stick in order to predict the objects present in the live video stream.

Project Title: ASN.1 To Java Compiler

To create a grammar file which contains the grammar rules of the data modeling language Asn.1 and to perform lexical, syntax and semantic analysis on the ASN.1 files and to produce ,if needed, the corresponding error messages. JavaCC parser is used to generate the parser for this compiler.