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Data Scientist

Boston, Massachusetts, United States
February 21, 2018

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Shantam Gupta

* ******* ******, *******, ** ***** 857-***-**** EDUCATION

Northeastern University (NU), Boston, MA, USA GPA 3.6/4.0 August 2016 – June 2018 (Expected) College of Computer and Information Science & College of Engineering Candidate for Master of Science (M.S.) in Data Science

• Relevant Coursework: Engineering Probability & Statistics, Data Management & Database Design, Supervised Machine Learning, Data Mining & Unsupervised Machine Learning, Introduction to Data Management & Processing, Special Topics in Data Science School of Technology, Pandit Deendayal Petroleum University (PDPU), Gandhinagar, INDIA GPA 8.03/10 June 2012 - June 2016 Bachelors of Technology in Mechanical Engineering


R, R Shiny, Python, Tensorflow, Keras, H2O, Azure ML, Jupyter Notebooks, SQL, Tableau, Hadoop, Pig, Spark, Power BI, Orange, Toad Data Modeler, MySQL, Weka, MATLAB, Microsoft Visual Studio, MS Excel, SolidWorks EXPERIENCE

College of Computer & Information Science, Northeastern University, Boston, MA January 2018 - Present Machine Learning Teaching Assistant

• Tutor for graduate level course - Supervised Machine Learning. Helped graduate students understand concepts about practical algorithms and supervised machine learning theory including topics but not limited to generative/discriminative learning, parametric/non-parametric learning, deep neural networks, support vector machines, decision trees, forests, etc. ( Level Education, Northeastern University, Boston, MA September 2016 - May 2017/ January 2018 - Present Level Core Analytics Teaching Assistant

• Coached over 100+ industry professionals across 4 different cities, to learn and apply concepts of Probability & Statistics, Business Intelligence, Data Mining, Data Visualization and Machine Learning by harnessing the power of analytical tools like MySQL, R, Tableau and Orange to industry sponsored capstone projects.

Level Education, Northeastern University, Boston, MA September 2017 - December 2017 Data Science Instructional Designer Co-op

• Developed course material, labs, recitation material and instructor guides for introductory and intermediate data analytics courses spanning topics from Probability & Statistics, Database Designing & Modeling, Data Mining, Data Visualization and Machine Learning. Charles River Laboratories, Wilmington, MA May 2017 - August 2017 Data Scientist Co-op, Advance Analytics Team

• Extensively worked on optimization of Long Short-Term Memory Networks(LSTMs), a type of Recurrent Neural Networks for Sales Quantity Prediction to anticipate demand for production. Testing reliability of other time series methods for long term forecasting.

• Designed a system to train a hundred Time Series models using LSTMs and performed a comparative analysis between the LSTMs and other time series models like ARIMA, Holts-Winter, Exponential Smoothing, etc. for short term forecasting. PROJECTS

Prediction of stock prices and change in its movement using LSTMs -RNN July 2017

• Designed and Optimized a Long Short-Term Memory Network (Recurrent Neural Network) for predicting stock price and the change in its movement for Charles River Labs (CRL) listed at NYSE. Detection of Fake News Posts on Facebook March 2017 - April 2017

• This project involved verifying the authenticity of news posts on Facebook. The news post and user comments were vectorized into a 300-dimensional vector space using Mikolov's skip gram model and combined in varied proportions. These vectors along with other user reactions were passed as features to various ML classifiers (used in high dimensional feature setting like Nearest Shrunken centroid) for predicting the class labels. Database Design and Modeling for a Cellular Company October 2016 - December 2016

• Designed a Database Model using Toad Data Modeler and Microsoft SQL Server for a Cellular Company. Also, developed a web application using RShiny (integrated with MySQL).

Recommendations for Dognition Business Process Change August 2016

• Formed a business process change proposal on increasing the numbers of tests users complete for Dognition Dog Company. This included analysis of the dataset, creation of dashboards and communication the results in the form of a data story using Tableau. Modeling Credit Card Default Risk and Customer Profitability June 2016

• Developed a statistical model using multivariate regression to predict the Credit Card Default Risk and customer profitability. Smart Handshake - MIT Media Labs Design Innovation Workshop January 2015

• Designed and developed a sleek attachment that blends in one’s daily wearables to share and store information using the handshake to trigger the transfer of data eliminating the need for business cards. CERTIFICATIONS

• Financial Markets by Yale University on Coursera

• Business Metrics for Data-Driven Companies by Duke University on Coursera

• Data Visualization and Communication with Tableau by Duke University on Coursera

• Managing Big Data with MySQL by Duke University on Coursera

• Introduction to Big Data by University of California, San Diego on Coursera

• Deep Learning with TensorFlow provided by IBM Cognitive Class.

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