Dr. Amit Kumar Kushwaha

Machine Learning Experience:

Deep Learning classification using Keras and TensorFlow, Neural Networks, CNN, RNN, LSTM, Auto Encoders, Decision Trees, Random Forests, Gradient Boosting, K-Nearest Neighbors, Principal Component Analysis PCA, XGBoost, Clustering Analysis, Logistic Regression, Linear Regression, Feature Engineering

Natural Language Processing:

Knowledge Graph, Embeddings, BERT, GPT-2, Text Analytics

Product:

Recommendation engine microservices, Chatbots

Engineering:

Familiarity with building data pipelines (e.g., ETL, data preparation, data aggregation, and analysis)                    Experienced in model governance

Tools:

Python, R, SAS – HPA, Azure, Transact and Hive SQL

• A KPI driven professional with cross-domain Expertise: Retail, Finance, FMCG/CPG, Telecom, Media House, Oil &Gas
• Skilled in mapping product and operational problems to machine learning models with intellectual and analytical rigor
• Skilled in translating analytics output to actionable recommendations and delivery
• Experienced in presenting ideas and analysis to stakeholders while tailoring data-driven results to various audience levels

• Always try to exhibit intellectual curiosity and a desire for continuous learning by publishing research papers and building models from scratch
• Always work towards persuading internal stakeholders within and outside Data Science groups towards building best-in-class solutions
• Experienced in allocating tasks and resources across multiple lines of business and geographies
• Provide change management leadership
• Experienced in setting up data science COE ground-up

Sling Media Bangalore                                                                                                                                                                    May 2020 to Present

Bangalore location head of Data Science and Machine Learning CoE Team (Team Leading and Individual Contributor)

• Guiding and heading core data science team of 12 members, responsible for the development, feedbacks, and appraisal cycles
• Responsible for running and owning the AI and ML product initiatives across recommendation, personalization, and advertising
• Working to improve various versions of recommendation engine using various algorithms
• Search engine optimization for more personalized results using deep learning frameworks
• Setting up the feature engineering mart for the data science models
• Responsible for expanding the team

Indian Institute of Technology, Delhi                                                                           Dec 2019 to May 2020

• D. Research Scholar
  • I have completed the mandatory coursework for my D.
  • Published research papers in the field of deep learning
  • Worked with Delhi Technical University as a consultant to set-up data science COE involving: Recruiting, Training, and setting up a platform
  • Working as an independent data science consultant helping government organizations to solve problems through data science

Gap Inc.,Hyderabad                                                                                                                 June 2019 to Dec 2019

Hyderabad location head of Data Science and Machine Learning CoE Team (Team Leading and Individual Contributor)

• Lead and managed core data science team of 5 members, responsible for the development, feedbacks, and appraisal cycles
• Worked on building a chatbot for catering to customer queries
• Worked on coming up with a customer lifetime value model from scratch using ensemble deep neural network
• Improvements in the existing recommendation engine built on collaborative filtering and deep neural network
• Built a feature engineering framework and machine learning model governance ground-up

Fidelity Investments Pvt. Ltd., Bangal                                                                                   April 2016 to June 2019

• Lead (Manager) (Data Science) (Team Leading and Individual Contributor)

  • Lead and managed the data science team, responsible for development, feedbacks and appraisal cycles
  • Involved in identifying, developing, and communicating business trends to business stakeholders
  • Involved in ideating requirements & design iteratively with business partners without formal requirements documentation

Lead (Manager) (Data Science) (Team Leading and Individual Contributor)

• Lead and managed the data science team, responsible for development, feedbacks and appraisal cycles
• Established predictive model governance pipeline
• Implemented an email un-subscription framework using a deep neural network model
• Improve campaign effectiveness using the XGBoost model
• Random Forest model to measure branches and opportunity effectiveness measurement
• XGBoost classifier for campaigns, DM/EM effectiveness measurement by identifying and developing key metrics
• Deep Neural Network Quantile Regression for Customer Lifetime Value
• Support Vector classifier to implement the next best offer

Accenture Applied Intelligence, Gurgaon                                                                              May 2011 to April 2016

• Consultant (Data Science) (Team Leading and Individual Contributor)

  • Managed and lead a team of 3 data scientists, responsible for the development, feedbacks, and appraisal cycles
  • Boosted Tree & Response models for customized targeting of each member with limited most relevant offers
  • Support Vector classifier to distinguish free user vs. paid user to implement the next best offer

Consultant (Data Science) (Team Leading and Individual Contributor)

• Managed and lead a team of 2 data scientists, responsible for the development, feedbacks, and appraisal cycles
• Media response curves automation using Bayesian statistics
• Principal component analysis for reducing features for the effectiveness of New Gen stores of the world’s largest Retail
• Neural network model to predict if Free Users will convert to a Paid subscription
• Bayesian Statistics to find the saturation curves for Long and Short-term impacts of marketing vehicles

SumTotal Systems, Inc. Hyderabad                                                                                         May 2006 to May 2009

• Expert (Machine Learning Initiatives) (Team Leading and Individual Contributor)

  • Oversaw one analyst responsible for the development, feedbacks, and appraisal cycles
  • Random Forest model for predicting the effectiveness of promotional campaigns and identifying important features
  • Naïve Bayes classifier for reducing the promotional email un-subscription

Analyst (Machine Learning Initiatives) (Individual Contributor)

• Logistic regression model for classifying Low, Medium and High performing discount coupons
• Principal Component Analysis for dimensionality reduction of features used for performance measurement of outlets
• Decision tree model for predicting Price Promotion sales

Predicting Information Diffusion on Twitter a Deep Learning Neural Network Model Using Custom Weighted Word Features

DOI: https://doi.org/10.1007/978-3-030-44999-5_38

• Language Model-Driven Chatbot for Business to Address Marketing and Selection of Products

DOI: https://doi.org/10.1007/978-3-030-64849-7_3

DOI: https://doi.org/10.1007/978-3-030-64849-7_22

• Studying Online Political Behaviors as Rituals: A Study of Social Media Behavior Regarding the CAA

DOI: https://doi.org/10.1007/978-3-030-64861-9_28

Department of Computer Science,
Indian Institute of Information Technology,
Lucknow, India.
[email protected]