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Data Information Technology

Jersey City, NJ
March 16, 2018

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Extensive (4+ years) experience in analytics space with a deep understanding of analytical methodologies and techniques

Experience in working with teams and engagements to solve business problems using data analytics

End-to-end experience in designing and deploying data visualization

Well versed in understanding, analyzing and applying algorithms and regression on data

Master’s degree in Computer Science (Analytics)

SKILLS: Languages: SQL, R, Python (NumPy, Pandas, SciPy, Scikit learn, Matplotlib), SAS, HTML, C, C++, Java, Linux

Methodologies: KNN, k-means, Decision trees, CART, Principal Component Analysis, Logistic regression, MANOVA, ANOVA, Multiple regression Analysis, Factor Analysis

Database Systems: RedShift, MySQL, SQL-Server

Visualization Tools: Tableau, Power BI

Software/Tools: GitHub, SQL-Workbench, AWS, Atom, Excel, PowerPoint, Eclipse

EDUCATION: Stevens Institute of Technology, Hoboken, NJ

Master of Science, Computer Science May 2017

Mumbai University, Mumbai, India

Master of Science, Information Technology May 2013

Bachelor of Science, Information Technology May 2011

PROJECT: RedShift Migration May-June 2017

Migrated in-house data to RedShift, performed quality checks on data to ensure format and correctness. Built a reporting layer (Tableau) on top of RedShift.

Built reports like what if analysis, LODs, Dual axis, Time series graph and Pie charts on Tableau desktop using Yelp dataset.

Environment: SQL workbench, Tableau 9, AWS Redshift

EXPERIENCE: United Nations Headquarters – Data Analyst November 2017 to February 2018

Worked on merging datasets from different sources using Tableau extracts and data blending for further visualization on final data set

Created interactive dashboards using filters, drill down and drop down menu with functionalities like dual axis, bar graphs, time series chart, bubble charts, pie graphs, line charts and heat maps

Connected Tableau server to publish dashboards and maintained accessibility to users

Involved in gathering data, merging and transforming into meaningful insights - creating pivot table, Vlookup, Hlookup and VBA in excel.

Generated SQL queries to document in user guide for future assistance to personnel

Created database in MS Access and generated Queries, Reports and forms.

Environment: Tableau 10, MS SQL, MS Access, MS excel

V.V Engineering – Associate Business Analyst July 2013 to November 2015

Performed customer segmentation depending on purchase behavior

Determined the minimum stock and profit margin by building a model that can group items into categories ‘fast moving and slow moving’ using k-means clustering

Gathered the requirements, designed and developed new reports (Gantt charts, bar graphs, bullet graphs) and enhanced existing reports and capabilities in alignment with business needs

Designed new data sources for developing analytical reports from multiple data sources like Microsoft SQL Server, Microsoft Access and other flat files

Used VLookup, HLookup and pivot tables for quick summary reports

Involved in developing UI and synchronizing Crystal reports with SQL server for a complete Invoice Application

Environment: MS Access, SQL Server, Visual Basics, Crystal Reports, MS Excel

SERVER WorldWide - Business Analyst August 2011 to April 2013

Predicted customers preference based on order history to maximize sales efficiency by developing forecasting model

Analyzed and summarized customer satisfaction survey data and produced yearly reports

Generated Visualization reports – timeline charts, Pivot charts and pie graphs

Created a data model for Sales data in MySQL DB

Created stored procedures and utilities to manage relational and dimensional data

Environment: MySQL, MS Excel

ACADEMIC Stevens Institute of Technology, Hoboken, NJ

PROJECTS: Revenge or Repent

Extracted, interpreted and analyzed data to identify key characteristics of an offender and transform raw data into meaningful information.

Created a classification model in R to predict if offender will be re-admitted to prison or not within 3 years of release from prison using KNN, Decision tree and random forest algorithms using dataset from

Contributing factors of Vehicles collisions

Performed data filtering, data cleansing and data encoding.

Developed a regression model to predict contributing factors of collisions caused by motor vehicles in boroughs of New York using Logistic regression on dataset from using SAS.

Analysis of Uber Trips

Developed a Business Dimension model on kaggle’s dataset for Uber and compared Uber trips and yellow taxi trips in outer boroughs of NY to conclude Uber are taking away trips from yellow taxis.

Visualized results in time series, bar chart and bubble chart using Tableau.

Yelp Anomalies

Established a model in Python to identify significant changes in average rating, through a one-sample t test, and then provided a brief summary of customer’s text for those periods using Yelp Businesses and Reviews files.

Created a bar chart representing the mean ratings per quarter and highlighted anomaly periods

Web Scraping

Implemented Web Scraping in Python using the beautiful soup library to search for similarity among the text from the page.

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