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Abhik Banerjee

Senior Software Engineer

Director Data Science and ML at Twin (Hiring)

San Francisco Bay Area

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Abhik Banerjee's Email Addresses & Phone Numbers

Abhik Banerjee's Work Experience


Senior Software Engineer

August 2006 to October 2008


Lead Software Engineer

November 2008 to August 2009


Machine Learning Intern

June 2011 to September 2011

Sunnyvale, CA

Abhik Banerjee's Education

rajendra vidyalaya

High School, Science/Computer Science

2000 to 2002

Utkal University

B.E/BTech, Computer Science

2002 to 2006

University of Cincinnati

MS, Computer Science- Machine Learning, (4.0/4.0)

2009 to 2012

Abhik Banerjee's Professional Skills Radar Chart

Based on our findings, Abhik Banerjee is ...

Problem solver

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52% Left Brained
48% Right Brained

Abhik Banerjee's Estimated Salary Range

About Abhik Banerjee's Current Company


Managing a team of 2 people. Manually testing the Deutche Bank softwares , and automating the test cases. Applications were based on Forex, Money Markets and Derivatives.

Frequently Asked Questions about Abhik Banerjee

What company does Abhik Banerjee work for?

Abhik Banerjee works for HCL

What is Abhik Banerjee's role at HCL?

Abhik Banerjee is Senior Software Engineer

What is Abhik Banerjee's personal email address?

Abhik Banerjee's personal email address is b****[email protected]

What is Abhik Banerjee's business email address?

Abhik Banerjee's business email addresses are not available

What is Abhik Banerjee's Phone Number?

Abhik Banerjee's phone (**) *** *** 906

What industry does Abhik Banerjee work in?

Abhik Banerjee works in the Computer Software industry.

Who are Abhik Banerjee's colleagues?

Abhik Banerjee's colleagues are Elena Fullman, Kymberly Sells, Kurt Kratchman, Erica Schumacher, Pramoda Vyasarao, Steven Smith, Rusty Lindsey, Teresa Short, Kevin Ruchlin, and Nabil Nawaz

About Abhik Banerjee

📖 Summary

Senior Software Engineer @ HCL Managing a team of 2 people. Manually testing the Deutche Bank softwares , and automating the test cases. Applications were based on Forex, Money Markets and Derivatives. From August 2006 to October 2008 (2 years 3 months) Lead Software Engineer @ McAfee Software QA Engineer - Product testing of different product suites for various clients , automating the test cases and re testing the bugs on a release basis. From November 2008 to August 2009 (10 months) Machine Learning Intern @ Proofpoint Apply Machine Learning algorithms (Unsupervised methods) to improvise the existing reputation systems , on a Hadoop cluster using Mahout algorithms / custom models. From June 2011 to September 2011 (4 months) Sunnyvale, CAGoogle ASL Training (Cloud and Deep Learning) @ Google This is an intense Training at Google Facilities partnering with Kohl's covering Deep Dive in the following areas (Google ASL - Advanced Solutions Lab)- Google Compute Cloud, Google Storage and DataProc- TensorFlow usage, and Training Deep Learning Models - CNN, RNN- Image Classification, Text Analysis, Language Models using Deep Learning and TensorFlow From February 2017 to March 2017 (2 months) Mountain View, CaliforniaSenior Data Scientist - Machine Learning, Big Data @ AOL -- Use supervised , unsupervised, semi-supervised methods, and natural language processing techniques for content clustering on AOL Mail date to do Mail Categorization, Mail segregation, Mail Clustering, Mail grouping and Understanding the Mail behavior.-- Building Classifiers for the Anti-Spam Team at AOL and applying various Data Mining and Machine Learning Techniques to Classify Spams and Hams. Improved % accuracy by 10+% on current anti-spam filters . From February 2012 to August 2014 (2 years 7 months) Sterling , VAComputer Science Graduate Student - Machine Learning Focussed Research @ University of Cincinnati I graduated from University of Cincinnati with a Master of Science degree in Computer Science . My Research area focused on Data Mining, Machine Learning and Natural Language Processing.Research Interests:- Data Mining, Web Mining, Information retrieval, Machine Learning, NLP.GPA- 4.0/4.0 From September 2009 to August 2012 (3 years) Student Researcher / Machine Learning @ Cincinnati Childrens Hospital Medical Center 1. (Web Development):- Working on JSP , AJAX , JPA , JavaScript , Apache Tomcat , Firebug , ORACLE SQL Developer for the maintenance and development of additional features for the following website - Worked on various Recommendation algorithms using Apache Mahout on Hadoop Architecture and other Recommendation Algorithms for Disease Data Sets , and Shopping data sets from Reclab.3. (Research work) :- Finding interaction between OMIM and OMIM based on the shared pubmed Ids , gene Ids , human phenotypes using clustering ,various other graph mining algorithms, and scoring techniques(Resnik's, Kappa score) to the data sets. From April 2010 to February 2012 (1 year 11 months) Data Science Manager/ Staff Data Scientist @ Kohl's - Leading Strong Data Science Research and Data Engineering teams in the areas of Machine Learning and Data Mining (Recommendations, Supervised and Unsupervised Learning techniques)- Worked with the core Google cloud team to move our ML jobs / Data pipelines to Google cloud platform, and run our Recommendation / personalization models to run on GCP environment.- Was first Data Scientist, Grew the team to 20+ Data Scientists and Data Engineers over a period of 2.5 years- Presenting strategic vision to C Level Executives (COO, CMO, CTO, CEO), how to empower business functions using Data Science- Hands on Experience in the areas of Data Mining , Machine Learning and Natural Language Processing (NLP) .- Personalized Recommendations, Personalized Search / Browse increasing overall digital revenue by 10+% - Sales Forecasting models, Customer segmentation, Customer Propensities for Ad Targeting, personalized Marketing Campaigns, Churn Prediction, overall customer engagement increment by 4%. - Deep Learning models for Retail Use Cases - Product Similarity, Fashion Labs (Mostly built on Tensorflow, Keras and Theano, using GPU AMI's in AWS)-Supervised and unsupervised techniques , Building Regression Based Models , Classification Models Naive Bayes, SVM ,Decision Trees, Adaboost, Neural Networks , Logistic Regression, Random Forest.) , Unsupervised Learning Techniques - Clustering, LDA, Topic Modeling.Tools :- Data Science / NLP - Python, R, Java, Scala, Matlab, Octave, Spark (Scala and Python), Weka, Mahout, Open NLP, Theano, TensorFlow, Keras, GPU, AWSBig Data - Hadoop, HBase, Hive, MapReduce, Scalding From August 2015 to July 2017 (2 years) San Francisco Bay AreaSenior Data Scientist @ Kohl's - Manage a team of Data Scientist's and Data Science Engineers for delivering Recommendations, and other Machine Learning solutions.- Applying Spark Streaming, and using Spark MLLib and GraphX for interesting use cases in Retail- Building Personalized recommendations for and other Kohl's channels- Leading a team of Data Scientists and Software engineers to solve various problems in Recommendation Systems, Online Personalized Ranking / Scoring Algorithms, Machine Learning and Natural Language Processing.- More Data more challenges From August 2014 to August 2015 (1 year 1 month) San Francisco Bay AreaCo-Founder @ AmiHunt Amihunt is a platform to buy and sell used items (very similar to Facebook Marketplace)- Worked on defining and implementing the Backend Architecture end to end (including Mongo DB, API layers, ML pipelines and models for recommendations, matching buyers to sellers.- Defined new Algorithms for Map based searches and finding nearest items and users for a better match- Hosting and Managing FE, middle tier and Backed DB services on AWS- The UI Design can be found here From August 2012 to August 2014 (2 years 1 month) Director of Machine Learning @ Twin - Disrupt the healthcare market , with chronic disease reversals ( not monitoring) and lead healthy lives - leading Machine learning , Data Science and Engineering Mountain View, California, United StatesDirector Data Science @ Oracle Leading a team of Data Scientists and Machine Learning Engineers at Adaptive Intelligence Apps (AI) Group - My team built an end to end ML pipeline on Kubernetes Infrastructure (using k8s, helm) on Oracle Cloud Infrastructure (this pipeline is responsible for Data Cleaning, Feature Engineering, Feature Selection, Model Training, Model Evaluation and Model Serving on top of the k8s infrastructure)- Hands on experience building and scaling ML pipelines from prototype to production . Leading a team of Fantastic Data Scientists and ML Engineers.- Using Kubernetes, Sklearn, Tensorflow, Seldon and other Big Data Technology components for building robust ML pipelines to run at scale, and moving end to end ML, Deep Learning models to Production- Responsible for delivering ML and NLP based (Traditional and Deep Learning) solutions in the areas of Recommendations , Personalization , Question - Answering solutions (AI Services) , and Lead scoring / Opportunity scoring use cases (AI Sales) From July 2017 to September 2020 (3 years 3 months) San Francisco Bay Area

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In a nutshell

Abhik Banerjee's Personality Type

Introversion (I), Sensing (S), Thinking (T), Perceiving (P)

Average Tenure

1 year(s), 9 month(s)

Abhik Banerjee's Willingness to Change Jobs



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