Summary
Overview
Work History
Education
Skills
MTech Thesis and Courses
Self Projects
Timeline
Generic

SHANKAR PAL

Summary

Professional with a robust foundation in data science and analytics, holding an MTech in Industrial and Management Engineering from IIT Kanpur. Completed an internship focused on machine learning, further honing technical skills in deep learning. Comprehensive knowledge in analytics and data science.

Overview

10
10
years of professional experience

Work History

Level 2 Analyst

Accordion
Hyderabad
05.2024 - Current
  • Developed an end-to-end automated process to source the data, preprocess it, and send email updates to the client.
  • Performed gap analysis on existing processes to identify areas of improvement.

Intern

Sarda Group
Nashik
05.2015 - 07.2015
  • Analyzed the gap in data capture and utilization in the Milk SBU.
  • Features are sorted according to their importance by the Random Forest Classifier.
  • Applied Random Forest model to classify the health status of cows based on selected parameters.
  • Find out several more useful features to track cows' health, against the rumination rate alone.

Education

M.Tech - Management Sciences

Indian Institute of Technology Kanpur
05-2024

B.Tech - Mechanical Engineering

National Institute of Technology Kurukshetra
06-2020

Skills

  • Python
  • Data Analytics
  • Statistics
  • Machine Learning
  • Deep Learning and NLP
  • SQL
  • Power BI
  • MS-Excel

MTech Thesis and Courses

  • Application of ChatGPT (or any other platform like it) in the field of Finance, especially in sentiment analysis of reports and effect of it on market.
  • Statistical Modelling for Business Analytics
  • Applied Machine Learning
  • Data Mining & Knowledge Discovery
  • Probability & Statistics

Self Projects

  • Amazon Customers Data Analysis - Developed an NLP based model to classify amazon reviews - Built deep learning NN using Keras which helped to achieve 73.85% specificity on complex text data.
  • Credit Default Prediction - Forecast whether a customer will default on their credit card - Applied Naïve Bayes, KNN, Logistic Regression, SVM, and Random Forest models, with hyperparameter tuning., Random Forest model performed best with 87% sensitivity and 82% AUC-ROC.
  • Image Classification, CNN - Predicted the emotion of animal in image using the CNN - Designed a CNN architecture with multiple convolutional layers, using libraries OpenCV, NumPy, Keras, and scikit-learn.

Timeline

Level 2 Analyst

Accordion
05.2024 - Current

Intern

Sarda Group
05.2015 - 07.2015

M.Tech - Management Sciences

Indian Institute of Technology Kanpur

B.Tech - Mechanical Engineering

National Institute of Technology Kurukshetra
SHANKAR PAL