AKSHUL AGARWAL

Boston, MA https://www.linkedin.com/in/akshulagarwal 617-***-**** ac4lxf@r.postjobfree.com EDUCATION:

Northeastern University, College of Engineering, Boston, MA Sep 2016 - May 2018 Master of Science in Engineering Management with certification in Data Analytics GPA: 3.6/4.0 Relevant Coursework: Data Warehousing and Business Intelligence, Computational Statistics, Data mining and Machine Learning, Probability and Statistics, Database Design and Management, Collecting Storing and Retrieving Data, Project Management University of Mumbai, Mumbai, India Aug 2011 - Jun 2015 Bachelor of Engineering in Computer Science GPA: 3.5/4.0 TECHNICAL SKILLS:

Languages: R, SQL, Python, Java. PL/SQL, T-SQL, C, C++, Matlab Database: SQL Server, MySQL, Oracle, PostgreSQL, MongoDB, Hadoop Data Integration Tools: Microsoft SSIS, Talend Studio Visualization Tools: Tableau, PowerBI, QlikSense, PowerPivot Software Tools: Microsoft Excel, SAS, SPSS, SQL Developer, Jupyter Notebook, Microsoft SSMS, MySQL Workbench, PGAdmin4, TOAD Data Modeler, Microsoft Visio, Jira, Confluence PROFESSIONAL EXPERIENCE:

Northeastern University, Boston, Research Assistant Oct 2017 – Jan 2018

Implemented a coding scheme for examining political ads

Adopted proposed coding scheme to annotate one of largest collection of political ads available to public till date

Evaluated, assessed and analyzed accuracy of quantitative research methods in extracting information from ads

Built dashboards in Tableau to present analysis results to lead PI and other researchers Analytics Advisory Group LLC, Austin, Data Science Intern May 2017 – Aug 2017

Executed a project to undergo a complete model development life cycle using CRISP-DM methodology for a healthcare client

Developed a prediction model in R using ARIMA to forecast heart related cases from inpatient discharge data

Selected ARIMA models with varied p,d,q values and validated it using AME, RMSE, MAPE parameters Itiviti AB, Mumbai, Associate Software Engineer Jul 2015 – Jun 2016

Managed complete software development life cycle starting right from requirement gathering and analysis to maintenance

Generated scripts, successfully tested and executed them to automate client order placing process

Migrated entire application on client’s machine and conducted UAT testing in production environment

Created dashboards in Tableau, QlikSense to depict trends in stock acceptance rates for various European stock markets ACADEMIC PROJECTS:

The Kaggle Project – Prudential Life Insurance Assessment Sep 2017 – Dec 2017

Interpreted dataset containing 127 predictors, narrowed them down to 38 using RFE and Variable Importance

Programmed a predictive model for risk classification using XGBoost, SVM, Decision Tree, Linear Regression algorithms

Compared different modeling techniques using RMSE values and selected best performing model Data Integration/Data Warehousing Sep 2017 - Dec 2017

Designed a Hybrid dimensional normalized target database consisting Fact and Dimension tables

Accomplished DI using Talend, SSIS involving source to target mapping, data-conversion, SCDs and error handling

Combined data from database tables using Tableau, PowerBI to depict trends, performance and profit margin Sentiment Analysis and Visualization of government policies using Twitter API Jan 2017 – Apr 2017

Mined data (16,00 tweets) related to government policies using Twitter API calls

Performed data wrangling in R and stored data in MongoDB

Devised an algorithm to perform sentiment analysis on data whose result was visualized using Tableau and ggplot Built a Health Insurance Company Database Jan 2017 - Apr 2017

Gathered and identified all key entities and relations and then designed database using Toad Modeler

Integrated Procedures, Triggers, Indexes & Functions to provide modularity to database

Created a front-end web application using R Shiny to access database and implement CRUD operations Speech Recognition and Authentication Aug 2014 – Apr 2015

Developed a MATLAB based application that would validate a user by speech recognition using feed forward neural network, achieving 82% speech recognition accuracy

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