Data Analyst Python

SHASHI PRABHA SAHU

Contact- +91-883******* *****-******************@*****.***

EDUCATION

• B.Tech, Information Technology, KIIT University, 2020 CGPA-8.3

• class 12, Senior Secondary School Sector-7, Bhilai 2016 Percentage-80%

• class 10, Senior Secondary School Sector-7, Bhilai 2014 CGPA- 8.4 WORK EXPERIENCE

Black Knight Financial Services Data Analyst, December 2019 to present, Full-Time

• Involved in analysing,designing, development, implementation, quality checking and curating data.

• Used backend technologies such as SQL, C#, Python for storing and retrieving data.

• Scrapped and manipulated data from different source using SQL.

• Done analysis on factors influencing the prices such as tax related data, property data etc for different type of counties. INTERNSHIP

DAWN, IIT Kharagpur Deep Learning Intern, January 2019 to June 2019

• Implement WideResnet Deeplearning Model to classify different plants disease.

• Achieved accuracy 90% on nodules data with class imbalance of 1:1 with just depth of 10 and widening factor of 5.

• Find the similarity between the two images by adopting feature vectors using lhash,phash algorithms.

• Experimented with trained models such as VGG, 2D-Resnet, Squeezenet for extracting the feature vectors of images.

• Achieved 91% sensitivity for nodules and 90% accuracy using novel Focal Loss Method for an inbalance class of 1:10. PROJECTS

Smartphone Application for Banking Technology

• Worked on Banking Chatbot Development for Android Smartphones using Dialogflow, Rasa NLU.

• Assemble and configure a backend server using Node.JS. App provides 24/7 online customer support to bank users.

• Build a RESTful API for the front-end to access backend services for testing. The bot is trained on the 4000 queries. Stock Prediction using Explainable AI

• Refined LSTM model using technical indicators to predict future price and to predict daily change in prices.

• Rigorously doing literature survey on mathematical, probabilistic which helps in predicting future stock prices.

• Implore (LRP) by assign relevance scores to input variables which predict deep neural-networks. Neural Network Models to Predict Stock Prices

• Objective: Compared the traditional methods with the state-of-art neural networks for stock price forecasting.

• Used two datasets Tadawul All Share Index and Dow Jones Industrial Average for the prediction of stock prices.

• Reduced MAPE from 2.21% to 1.46% and 16.12% to 2.5% prediction on both datasets by using best neural model. Machine Learning

• Evolved the Decision Tree algorithm in python to solve a real-world classification problem with different gain metrics.

• Implemented a Multilayer Neural Network in python to classify a messages as SPAM. Online Quiz system ‘Technical Quiz’

• Developed an Android App named ‘Technical Quiz’ which provides online based quiz with multiple choice question.

• Quiz application will support android base operating system. With this application, users or any organization can per- form actions like Administrative Task and Interview Task. Project on text based sentiment Analysis using Naive Bayes Classifier

• Objective: Detect Human sentiments whether it is positive, negative or neutral using naive bayes classifier.

• Tokenized the data followed by cleaning involving removal of stop words and pre-processing text data to perform feature extraction using methods like natural language toolkit.

• Classified data using supervised learning to calculate polarity of statement whether positive, negative or neutral. TECHNICAL SKILLS

• Programming Languages-C, Java, SQL, Python, .Net, C++, R Fields-Machine Learning, AI, Data Science

• Software Skills-Android Studio, Netbeans, Firebase Others- Node.Js, REST API, MongoDB, Tensor Flow, PyTorch COURSEWORK INFORMATION

Computer Network,Software Engineering, Formal Automata, Database Management System, Operating System, Machine Learning, Artificial intelligence, Discrete Structures, Algorithms and Data Structures, C Programming, Spring Boot AWARDS

• Amongst top 50 student selected for India’s best engineering students, Economic Times appeared by 50,000 students.

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