Ashish Gupta

Data Scientist | Engineer | Business Analyst

San Diego, California


I am currently a Data Scientist for Qatar Airways and I specialize in Applied Data Science, data-driven Customer Relationship Management(CRM) solutions, Next-Best-Action recommendation systems, Revenue/Risk Management solutions, ETL/Data Engineering, reporting and analysis using state-of-the-art technologies in the market. Prior to this, I have worked with Ernst & Young for two plus years as a technology consultant and with the experience of deploying cross-domain data science projects, I have found my passion in making sense of complex data patterns with the objective of improving business application.


  • Applied Machine Learning
  • Recommender Systems
  • Churn and Risk Management
  • Data Visualization
  • Trend Forecasting
  • Fraud Analytics
  • Deep Learning


  • Master of Science in Business Analytics, 2020

    University of California, San Diego

  • Bachelor of Engineering in Electronics and Communication, 2017

    SJCE, Mysore, India



Data Scientist

Qatar Airways

Sep 2020 – Present New York
  • Worked closely with leadership in developing an automated python flask-based web-application for identifying network opportunities and threats to QR market share, drastically reducing the conventional man-hours required
  • Worked on market segmentation at the booking level using complex business rules and scoring systems on IATA datasets using pySpark on Azure DataBricks; thus, improving campaign performance and maximizing revenue
  • Part of the global Central Business Intelligence team, my structural tasks also include validating data integrity, standardizing key RM data practices at a company-wide level using Tableau, maintaining pipeline systems for recurring data streams and ad-hoc querying using Dremio data lake and SQL for business applications

Lead Data Consultant


Apr 2020 – Jun 2020 San Fransisco, California
  • Worked on deploying a robust ML pipeline for credit risk management by sifting through 400GB worth public information and finding patterns in SMS, call and social media usage; with the objective of reducing loan defaults in the company’s fintech app
  • As the team lead, my tasks also included planning, monitoring and communicating analytical solutions to stakeholders across business in an agile software developmental cycle

Graduate Student Researcher

Computer Science & Engineering Department

Jan 2020 – Mar 2020 University of California, San Diego, California
  • Worked on machine learning techniques like transfer learning and semi-supervised domain adaptation to map modern building infrastructure information to a common schema for unified interpretation and scalability
  • Implemented adversarial discriminative domain adaptation using functional keras and tensorflow in linux python

Technology Consultant

Ernst & Young

Jul 2017 – Jul 2019 Bangalore, India
  • Worked closely with a client in designing a credit risk assessment application featuring credit analysis and score generation using customer data on Pega; leading to decrease of manual efforts by 24 hours per week
  • Developed a call centre software application for an insurance firm suggesting next best action and intent tasks to customer representatives based on previous interaction history; reducing the average response call time by 2 minutes
  • Collaborated with the state government of Andhra Pradesh, India to develop and deploy a unified data-based platform collecting large dataset of public information, using SQL to perform ETL on this data
  • Led a team of five to develop an internal EY asset using NLP to automate customer feedback classification by applying SVM classifier algorithm to segment emails based on text content improving the speed of processing requests by 60%

Data Analyst

Surabhi Softwares

Feb 2017 – Jun 2017 Mysore, India
  • Performed time series analysis for yearly profits and expenditure using autoregressive moving average method in python providing a comprehensive dashboard display of cost and revenue models for business decisions
  • Identified key metrics most impactful in business growth using correlation-regression analysis on business verticals revenue streams; resulting in quarterly profit margin increase by 25%
  • Generated weekly company insights and reports by using Tableau’s data visualization features

Operations Analyst

Kaynes Technology

May 2016 – Jun 2016 Mysore, India
  • Analysed bottlenecks in the process of manufacturing printed circuit boards from raw material procurement to quality control improving efficiency by 20% in terms of PCB output by optimizing labour-task assignment



Domain Adaptation using ML Transfer Techniques

Semi-supervised domain adaptation to map modern building information

GRP and Reach estimation for unrated TV ad-spots

Developed a Gradient Boosting regression model to predict the reach for unrated TV advertisements

NGO Donation request optimization using AWS SageMaker

Developed a classification model to predict individual income for optimizing donation requests for NGOs

TextCraft - An asset for text analytics

A dynamic user-friendly interface for analysis of topics and sentiments in text documents

Start-Up Global

Predicted the rank of a country in terms of Ease of Doing Business(EODB) in 2019 using Deep Learning

Modular Survey System with Data Analytics

Developed a customisable survey system which uses Logistic Regression to predict a categorical survey information


Machine learning oriented gesture controlled device for the speech and motion impaired, ICDMAI'17, Pune, India

This paper proposes the idea of using machine learning implementation to develop a device that can benefit the speech and motion …

Ramifications of machine learning in the manufacturing sector, RTCSE'17, Kuala Lumpur, Malaysia

This paper provides insight to how machine learning could disrupt the manufacturing development in India and could result in better …

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