Resume

TL;DR - Download my full resume here.

About

I am Shravan Venkataraman, Co-Founder at Hankavalshier’s. I will soon be pursuing a research Masters in Computer Science, exploring my research interests. My research interest is in Large-Scale Machine Learning, specifically in optimizing Deep Learning for applications with strict latency requirements, driverless cars, high-frequency trading, and search engines for instance. I will be exploring the topics of continuous training and online learning, during my Master’s Research.

Education

Master of Science in Software Engineering, 2010 - 2015

VIT University | Vellore, India

University Rank: 3/337 ; GPA: 9.34/10
Merit Scholarship awardee for 4 years, for consistently being in the top 10 ranks.

Higher Secondary Examination, 2009 - 2010

Sri Sankara Vidyalaya | Chennai, India

GPA: 92%

Experience

Hankavalshier’s, Jul 2017 - Present

CTO, Director of Marketing Research | Chennai, India

Developed strategies and A/B tests for B2B \& Social Media Marketing.
Built a lead-generator using curated restaurant information provided by ZomatoAPI, to conduct data experiments.
(Python, R, Excel)

Independent Trading, Jul 2017 - Present

Derivatives & Equities Trader | Chennai, India

Managing a portfolio of INR 2M, spread across different equity \& debt instruments.
Developed algorithmic trading strategies using statistical analysis, language processing, and machine learning techniques.
(Python, Selenium, Pandas, Excel, Pytorch, NLTK, Tensorflow)

PayPal, Jan 2017 - Jul 2017

Software Developer II | Chennai, India

Worked with Admin, Global Operations, Shipping, and Marketplaces teams in onboarding \& integrating funds availability APIs and services.
Implemented seller-fraud prevention features and saved over $5M per annum in losses for PayPal. Developed asynchronous messaging systems to handle buyer/seller emails, to block access to funds, and to release funds. Migrated the Funds Availability email pipeline from legacy stack to YAM messaging system.

PayPal, Jul 2015 - Dec 2016

Software Developer I | Chennai, India

Migrated the Risk Fraud Restriction product from legacy stack to Java based stack and helped deprecate the legacy stack by over 40\% in 6 months.
Created large-scale systems including web services, REST services, daemons, and libraries for Risk Funds-Availability team.
(Java, C++, Unix, Eclipse)

PayPal, Jan 2015 - Jun 2015

Software Developer Intern | Chennai, India

Developed a custom querying \& semi-automated statistical reporting system for the Technical Management Team.
Reduced the total number of man-hours spent on the reporting process by 85\% and built a dashboard for the same.
(Python, Django, Excel, Javascript)

VIT University, Jul 2012 - Dec 2014

Teaching Assistant | Chennai, India

Teaching Assistant: Problem Solving Using C, Data Structures \& Algorithms, Programming in Java courses. Taught a batch of 25 students for a grade improvement program. Graded quizzes, assisted instructor in checking the test papers, guided students in weekly problem-solving lab sessions.
Lab Student in-charge: Software Metrics Lab and Software Testing Lab.

Technical Skills

Languages: Python, R, C++, Java, SQL
Tools: LATEX, Excel, MATLAB
Libraries: Pandas, Pytorch, Tensorflow, NLTK, Matplotlib, Scikit-Learn, Numpy, Scipy

Coursework

Math: Applied Probability & Statistics, Linear Algebra, Discrete Mathematics, Multivariate Calculus.
CS: Artificial Intelligence, Theory of Computation, System Programming, Operating Systems.
Audited MOOCs: Algorithms (Princeton), Statistics with R (Duke), Data Science (JHU), DeepLearning.ai.

Projects - Research/Development

Cryptocurrency Price Prediction Using Deep Learning

ALGORITHMIC TRADING | June 2018 - Sep 2018

Developed a volatility driven trading strategy for Cryptocurrencies with the time-series from Kaggle.
Implemented two models to predict the nature of change of price relative to current time: A neural-network with one hidden layer and a ReLU activation function \& a Deep Learning model based on LSTM.
(Python, Scikit-Learn, Numpy, Scipy, Pytorch)

Tesla Stock Price Change Prediction Based on Elon Musk’s Tweets

ALGORITHMIC TRADING | June 2018 - Sep 2018

A hybrid prediction model that combines a time series neural network model and a language processing model.
Implemented an ARIMA model that tracks and predicts the time series data of Tesla stock and a language processing model that uses a gaussian process with bag of words feature vectors and fixed rule multi-kernel learning for sentiment analysis of Elon’s tweets.
(Python, Scikit-Learn, Numpy, Scipy, Pytorch, NLTK)

Statistical Analysis & Modeling Projects

ALGORITHMIC TRADING, Jan 2018 - Jul 2018

Implemented Black-Scholes \& Binomial Option Pricing Models.
Constructed an equal weighted portfolio of NASDAQ stocks for optimal tracking error, sample-size, and returns.
Performed exponential smoothing \& forecasted stock prices using Linear Regression.
Performed an empirical study on the performance of Indian Gold \& Equity ETFs for statistical arbitrage opportunities.
Conducted a statistical analysis study on performance of IPOs in India and studied a potential investment strategy.
(Python, R, Excel)

Predicting Stock Price Change Using Sentiment Analysis

ALGORITHMIC TRADING, Oct 2017 - Mar 2018

Applied a classifier-predictor model using Naive-Bayes classifier algorithm to tweets and news headlines.
Implemented a multi-label classification algorithm to identify the risk factors from SEBI filings of NIFTY50 stocks using K-Nearest Neighbor algorithm and predicted the possible nature of change in price.
(Python, Selenium, Excel, Pandas, R, NLTK)

B2B Lead Generator Using Restaurant Information \& Text Analytics

HANKAVALSHIER’S, Jul 2017 - Mar 2018

Utilized the countrywide restaurant information curated and provided by ZomatoAPI to create data-visualizations and build analytics reports.
Applied text-mining using high efficiency Support Vector Machine (SVM) model to restaurant reviews and identified the potential matches in restaurants. Improved the lead-generation and client-conversion rate from 20% to 65%.
(Python, R, Excel)

Evaluating Neural Networks For Time-Series Forecasting

UNDERGRADUATE THESIS, Jul 2013 - Dec 2013

Evaluated reinforcement learning approaches and optimization methods for the time-series forecasting problem.
Proposed a two-step hybrid model using neural networks to forecast the exchange rates of five currency pairs. Final model trained with Levenberg-Marquardt algorithm to forecast currency exchange rates with ~95% accuracy.
(MATLAB, Excel)

Course Projects

VIT UNIVERSITY, Jul 2010 - Dec 2014

Lymphatic Filariasis Reporting System: A Healthcare web application for managing the progress data of Filariasis patients. (MySQL, PHP, CSS, HTML5)
Online Hostel Counseling Management: A pilot web application to manage the hostel counseling processat VIT and thereafter manage student data throughout the year of stay. (C#, ASP, CSS, Oracle)
Cloud Based Software Version-Control System: Built a cloud based small scale dev-ops version control system for the course department. (Ruby on Rails, Node.js)

Academic/Extracurricular Awards & Leadership Achievements

Co-founded an artisanal food products manufacturing company, led a team of seven, built a data driven market research strategy, improved revenues by 7x, profits by 4x between 2016 and 2018.
Chancellor’s academic excellence merit scholarship awardee (top 10 ranks) 2011 - 2015.
Mentored pre-final year students at VIT University as part of a career fair workshop.
Coordinated the intern-show off, won the Best intern product and Best poster-design prize, and was awarded INR 10,000.
Coordinated PayPal’s India product showcase challenge and built an internal leaderboard tool (using Node.js and MongoDB) to track the results real time. Hosted the challenge and compered the events.
Was part of a team of 5 which stood 3rd in the PayPal Risk Hackathon 2016.
Won a poetry competition conducted by the VIT English Literary Club.
Led the team that won the PayPal Annual Cook-Off Challenge 2016.