CHIRAG PURSHOTTAM PIPALIA

adcndu@r.postjobfree.com https://www.linkedin.com/in/chiragpipalia 973-***-**** SKILLS AND CERTIFICATION

●Languages and Tools:Python (Keras, Numpy, Scipy, SciKit-learn, NLTK, Pandas, Matplotlib), C++, R, SQL, AWS

●Coursera:Deep Learning Specialization. (Credential ID: L8KQUZHL3GHY) WORK EXPERIENCE

Argus Information Services White Plains, NY

Data Scientist Jul 2018 – Present

●Predictedcleanmerchant identifiers with an accuracy of 82% and matching it to a unique location to be used for analysis across various teams, generating significant revenue across multiple projects

● Implemented entity recognition system using RNN to extract merchant and location attributes from unstructured transactions

●BuiltDBSCANclusteringmodel to de-dupe list of location level store data sourced from multiple 3rd party merchant aggregators, thus improving the quality of match by 30%

● Implemented web scraping framework to gather recent and accurate location data accounting for closed and newly opened stores

●Used memory mapping, parallel computing and generators to increase computational efficiency and memory usage OptionsPlay New York City, NY

Data Science Intern Jan 2018 – May 2018

●Generated sector and company level sentiment signals based on high frequency financial news data using Deep ConvNets to its predict impact on stock performance

●Trained a pre-trained word vector on financial news data to capture the semantic relationships between financial terms BlackRock/ Rutgers Business School Newark/ New York City Machine Learning Researcher Jun 2017 – Sep 2017

Worked with the Head of Liquidity Research at BlackRock on using machine learning to develop a solution to predict mortgage prepayment.

●Applied RNN machine learning techniques such as LSTM and Gated Recurrent Unit (GRU) using Keras to predict mortgage prepayment.

●Achieved accuracy ranging from 76% to 81% and evaluated results with those of logistic regression based on f1-score and ROC curve (AUC score: 0.65)

KPMG Mumbai, India

Cyber Security Analyst Jun 2015 – Jun 2016

● Implemented Random Forest to detect phishing websites for various companies in telecom domain and thus reducing the user information leak and fraudulent activities due to phishing attacks

●Took initiative and built a model to extract tweets to identity for malicious users and tweets causing reputational adversity to the client by compromising client’s internal information on the social media platform. Built machine learning model to identify tweets pertaining to information leak

Accenture Services Private Limited Bangalore, India Associate Software Engineer Nov 2013 – Dec 2014

●Implemented various automation frameworks using Python enhancing the operational efficiency by 40%. Supported IT infrastructure using technologies which include Active Directory, SCCM, SCOM PROJECTS

Neural Machine Translation with Attention using GRUs Nov 2017 – Dec 2017 Implemented an encoder decoder network using bidirectional RNN as encoder and unidirectional RNN as decoder with attention mechanism between them. Also applied beam search and pre-trained FastText embeddings Facial Expression Recognition (ConvNets and RNN) Mar 2017 – Apr 2017 Explored Recurrent Neural Network as a possible solution for image processing. Implemented facial expression recognition system using ConvNets and LSTM to detect discreet facial expressions and achieved an accuracy of 62%. EDUCATION

Rutgers Business School Newark, USA

Masters in Quantitative Finance Aug 2016 – May 2018 Courses: Statistics and Machine Learning, Financial Time Series, Econometrics, Object Oriented Programming. University of Mumbai Mumbai, India

Bachelor of Engineering in Electronics and Telecommunication Aug 2009 – Jun 2013

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