Summary
Overview
Work History
Education
Skills
Certification
Key Result Areas
Specializationandframeworks
Pythonlibraries
Languages
Projects
Database
Timeline
Generic
Abhishek Gupta

Abhishek Gupta

Data Scientist
Gurgaon,HR

Summary

A result-oriented professional with an analytical bent of mind, offering nearly 7 years of experience in Data Science and Analysis; resourceful in performing data analysis, data pre-processing, and feature engineering in support of Advanced Machine Learning algorithm development

Overview

7
7
years of professional experience
5
5
Certifications

Work History

Data Scientist

BharatPe
06.2020 - 08.2021
  • Devising and implementing data-driven strategies to enhance growth including revenue and profits using Statistical/ Predictive Models and Machine Learning Algorithms utilizing diverse sources of data

Lead Analyst

Barclays
09.2021 - 03.2022
  • Executing all Data Science activities and implementing Machine Learning techniques

Data Scientist

PNB MetLife
03.2022 - Current

Developed machine learning models to predict early claims for multiple channels.

Developed machine learning models to predict non persistent customers.

Developed model to identify customers for PASA.


Data Scientist

Adnet Global
01.2019 - 12.2019
  • Implementing demand forecasting models which can improve upon forecast accuracy and developing pipelines to analyze large simulation datasets

Data Scientist

PharmEasy
06.2017 - 12.2018
  • Building models to address business problems

Education

Advanced Management Program in Business Analytics -

Indian School of Business (ISB)

Post Graduate Program in Data Science & Business Analytics - undefined

Aegis School of Business & Data Science

B.Com. (Commerce) - undefined

Delhi College of Art, Delhi University

Skills

Project Execution & Management

Certification

Introduction to Deep Learning, Data Camp, 2017

Key Result Areas

  • Executing all Data Science activities and implementing Machine Learning techniques
  • Devising and implementing data-driven strategies to enhance growth including revenue and profits using Statistical/ Predictive Models and Machine Learning Algorithms utilizing diverse sources of data
  • Interfacing with stakeholders to identify opportunities for leveraging company data and using predictive modeling to increase & optimize customer experiences & other business outcomes
  • Implementing demand forecasting models which can improve upon forecast accuracy and developing pipelines to analyze large simulation datasets
  • Performing cleaning of data which includes understanding & removing unnecessary & repetitive data
  • Conducting Root Cause and Trend Analysis on negative impacts to system resources to help establish and maintain Service Level Agreements
  • Designing prediction algorithm using advanced data mining algorithms to classify similar properties together
  • Managing the end-to-end implementation of various projects, encompassing design, development, and coding
  • Writing automation codes for data cleansing, manipulation, and analysis
  • Assisting with data gathering strategies to ensure alignment with corporate goals and objectives

Specializationandframeworks

  • Machine Learning
  • Deep Learning
  • Statistical Analysis
  • Web Scraping

Pythonlibraries

  • Tensorflow
  • Keras

Languages

Python
R
English
Hindi

Projects

Barclays, Probability of Default, Calculated probability of Default for housing loan and credit card application using various modeling techniques. BharatPe, Time Series Anomaly Prediction, Predicted anomalies in the frequency of transactions on real-time data. Used Python and Prophet for the same. BharatPe, Classifying Transacting and Non-Transacting Merchants, Within 15 minutes of on-boarding, the time model could predict whether merchants would transact or not with 85% accuracy. This model brought down operations costs by 25%. Used SMOTE and Random Forest. BharatPe, Credit Risk Modelling, Built a credit risk model for disbursing loans based on various features such as Experian score, number of delinquencies, credit card, and so on. Used an ensemble of XGboost and Random Forest; scrapped contact information of customers from the undisclosed website for targeting new products to them. Adnet Global, Face Recognition, Built face recognition for identifying various Hollywood celebrities for UK-based fashion magazines. Used Python, OpenCV, dlib. The model could identify 90% of the celebrities correctly. Adnet Global, Time-series Forecasting, To fulfill the gap between demand and supply of human resources, time series forecasting was done to identify the demand for services. Projects were very seasonal, so SARIMAX and R were used which led to a reduction in cost by 40% PharmEasy, Prescription Recognition, Built an image classifier for identifying valid and invalid prescriptions. Used Python, OpenCV, and Resnet which reduced workforce cost by 30%. PharmEasy, Customer Segmentation, Clustered customers into 4 clusters based on usage patterns, this helped the Marketing Team to run targeted campaigns. PharmEasy, Database of Doctors, Built a database of doctors using Selenium and Beautiful Soup.

Database

  • SQL
  • NoSQL

Timeline

Data Scientist

PNB MetLife
03.2022 - Current

Lead Analyst

Barclays
09.2021 - 03.2022

Data Scientist

BharatPe
06.2020 - 08.2021

Data Scientist

Adnet Global
01.2019 - 12.2019

Data Scientist

PharmEasy
06.2017 - 12.2018

Advanced Management Program in Business Analytics -

Indian School of Business (ISB)

Post Graduate Program in Data Science & Business Analytics - undefined

Aegis School of Business & Data Science

B.Com. (Commerce) - undefined

Delhi College of Art, Delhi University
Introduction to Deep Learning, Data Camp, 2017
Machine Learning Toolbox, Data Camp, 2017
Supervised Learning with scikit-learn, Data Camp, 2017
Introduction to Text Mining, Data Camp, 2017
Data Visualizations in R, Data Camp, 2017
Abhishek GuptaData Scientist