Senior Applied Scientist at Amazon
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I am an Experienced Machine Learning Research Scientist with a history of working in the Data Science RnD space for nearly 10 years. Holder of 9 granted patents and first author of multiple top tier conference papers. Google Scholar Link: https://scholar.google.com/citations?hl=en&user=EMOEhWwAAAAJ
Indian Institute of Technology, Delhi
Master of Technology (MTech), Computer Technology
January 1, 2014 – January 1, 2016
National Institute of Technology Durgapur
Bachelor of Technology (B.Tech.), Electronics and Communication Engineering
January 1, 2010 – January 1, 2014
Amazon
Senior Applied Scientist
April 1, 2023 – Present
Amazon
Research Scientist II
May 1, 2020 – March 1, 2023
Accenture Labs
Technology Research Associate Principal
December 1, 2018 – May 1, 2020
Bangalore
Accenture Labs
Technology Research Specialist
September 1, 2017 – November 1, 2018
Bangalore
Opera Solutions
Analytics Specialist
July 1, 2016 – August 1, 2017
Noida Area, India
CERN
Research Associate at European Organisation for Nuclear Research
May 1, 2013 – August 1, 2013
Geneva, Geneva, Switzerland
Spend Classi fication using Convolutional Neural Networks
February 1, 2017 – June 1, 2017
Used deep learning paradigms to classify spend data of a Fortune 500 company. 1.Re-purposed concepts from latest machine learning models built for text sentiment analysis to classify free text spend data comprising of: supplier's name, general ledger account information, and unstructured free-text information, such as purchase-order description, purchase-order line description. 2. Used Convolutional Neural Networks and Word2Vec to achieve a 13 percent lift in accuracy over the baseline multinomial Naive Bayes model.
Optimization of E-Mail marketing strategy
August 1, 2016 – Present
Used given historical data to derive descriptive signals describing customer behavior, and use those descriptive signals to build predictive signals for predicting customer response. Helping the design of a better E-Mail targeting system.
Large Scale Entity Match problem
July 1, 2016 – February 1, 2017
Organisation of an Unstructured Database of company names for a leading professional services company by Clustering the entities within the database of 4.2 mil so that affiliated companies come together. Given a new entity identification of prospective affiliates and duplicates within the database becomes easier and more efficient. The modifi ed search engine brought up 18% more affiliates on an average for 5000 queries within top 50 ranks as compared to the old system.
Design of in-vehicle Driver Assistance Systems
June 1, 2016 – Present
A framework for a driver assistance system that uses computer vision based techniques to provide the driver an improved sense of the periphery.
Image Search Engine using CNN features
March 1, 2016 – Present
A python based system for fast retrieval of images similar to a query image from a large database.Used features extracted from a deep learning architecture for indexing the images.
Exploration of object detection and recognition using Deep Learning techniques
November 1, 2015 – Present
Survey and implementation of deep learning based methods for object detection and recognition in images and video. Also practised using deep learning models on the standard MNIST database
Spam Classifier
August 1, 2015 – Present
Developed a SVM based spam filter application using data from SpamAssasin database.
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from image search engines to large-scale entity matching and driver assistance systems, indicates adaptability and a broad interest in applying AI across various domains. Their experience in both research-focused labs (Accenture Labs, CERN) and product-driven environments (Amazon, Opera Solutions) suggests a versatile approach to problem-solving and a potential fit for organizations that value both innovation and practical application. The consistent progression in roles and responsibilities, including leading teams, aligns well with a senior-level cultural expectation of ownership and mentorship.
Soft Skills & Operational Fit
The candidate's career progression and leadership roles at Amazon and Accenture Labs suggest strong leadership, problem-solving, and project management skills. The descriptions of leading teams and driving research indicate good collaboration and communication abilities. The awards received further highlight a proactive and high-achieving work attitude.