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Data Engineering

New York City, NY
February 19, 2020

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Phone: +1-551-***-**** Email: LinkedIn: Github : Summary

Graduate student at Columbia University with experience and passion for Data and Business Analytics and Quantitative Analysis. Engineering background coupled with coursework at Columbia equips me with technical acumen required to drive innovative and strategic business decisions while working with several cross-functional teams. Skills

Functional: Machine Learning, Data Analytics, Data Visualization, Data Mining, Project Management, Product Development, Financial Analysis, Git Programming: Python (Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn), SQL, C++, R, HTML Analytical Tools and Software: Tableau, Power BI, MS Excel, PowerPoint, Weka, Hadoop, MATLAB, Django, Gurobi Databases: MySQL, PostgreSQL

Work Experience

Student Data Scientist at Balyasny Asset Management – New York Jan 2020 – Present

· Analyzing technical indicators to observe non-linear relationship between future price stock movement & historical price and volume

· Performing feature engineering to build a trading model by using 190+ independent features

· Generating trading signals using technical indicators to provide assistance in investment and portfolio optimization Manager, graVITas’18 at VIT University, Vellore, India Jul 2018 – Oct 2018

· Led a two tier 30-member team in documenting assets worth $80,000 and registration of 7000+ participants

· Identified risks and ensured quality management by channelizing feedback over 4 times each week

· Served as the nexus for inter department communication to reduce silos within 9 different teams and reduced operating time by 20% Data Analytics Intern at National University of Singapore - Singapore Dec 2017 – Jan 2018

· Analyzed data of a car insurance company to understand customer behavior for delivering bidirectional value

· Designed a predictive model for providing appropriate insurance amount to the customers and helped reduce loss over 30%

· Implemented Logistic Regression and Random Forest algorithm using R and obtained an accuracy of 89%

· Incorporated the fundamentals of Hadoop Distributed File System to deploy a multi node Apache Hadoop cluster Product Analyst Intern, Rail Automation - Production Unit at Siemens - Bangalore, India Jun 2017 – Nov 2017

· Fabricated Interlocking System using Electronics Interface Cards for automation of railway signals

· Identified key organizational strengths and weaknesses to reduce risk in implementation of the Interlocking System

· Provided executives with data driven frameworks used as basis for production strategies Education

Master of Science in Business Analytics - Columbia University, New York Expected Dec 2020 Coursework: Machine Learning, Database Management, Business Intelligence, Probability, Statistics, Financial Analysis, Operations Strategy GPA: 3.66 on a scale of 4.0

Bachelor of Technology in Electronics and Communication Engineering - VIT University, Vellore, India May 2019 Coursework: C++, Business Analytics, Operations Research, Neural Networks and Fuzzy Control, Computer Organization and Architectures GPA : 9.31 on a scale of 10


· Bloomberg Market Concept Bloomberg Portfolio Management Projects

Content-Based Movie Recommendation System (Python, Libraries: pandas, NumPy, nltk, matplotlib)

· Extracted data from TMDB using APIs and performed Exploratory Data Analysis using pandas for 30,000+ movie data

· Performed text mining on movie overviews to create word clouds using the NLTK and Matplotlib libraries

· Identified two main searching criteria among users – movie title and keywords to execute content-based filtering

· Implemented Shortest Path, Cosine Similarity and TD-IDF methods to deploy an engine to recommend movies under 10 seconds

· URL: recommendationengine

Portable ECG Device (Excel, Python)

· Created a portable device that takes in ECG signal from the patient and detects presence of heart diseases

· Planned and executed classification algorithms to validate the result and achieved an accuracy of 85% Census Income Classification (R, Tableau)

· Led a team of 4 engineers in analyzing US census data available in the UCI machine learning repository

· Performed EDA of independent variables and monitored KPIs using Tableau to gain insights on the predictive power of the variables

· Executed a predictive classification task to determine whether individual income exceeds $50K/year

· Achieved 84.8% accuracy of prediction using Logistic Regression and 86.32% by Boosting algorithm Real Time Adaptivity of Network and its Analysis using Machine Learning (Excel, Python)

· Formulated a multiple base-station cellular network model based on user density to enhance QoS and QoE by 10%

· Performed DBSCAN algorithm on Geolife trajectories data to obtain user trajectories from over 2,000,000 mobility pattern

· Presented the paper at the International Conference on Science, Engineering & Technology, 2018 Leadership and Awards

· Organizer – ITSFEW International Conference (powered by SPRINGER) Social Volunteer - Red Cross Society

· Recognition Award by VIT for outstanding work in the development and operations domain in university fest

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