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Aspiring SAS Data Analyst

Kearny, New Jersey, United States
January 10, 2018

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Manaswini S. Thakur Phone: (201)-***-**** Email:

Tenacious Quest for Success + Ability to Learn Quickly. Completed Master’s degree in Data Science and has blend of technical skills, business acumen, critical thinking, and interpersonal skills to succeed in the domain of Business Intelligence and Data Analytics.


Base SAS

Accessing different data sources; SAS Formats; Data Manipulation using Functions, DO Loops, Arrays, and Conditional Statements; Generating Summary Reports and Frequency Tables.

Advance Excel

VLOOKUP, Pivot Tables, Charts, Macros, Formatting, Array Formulas, and Linear Optimization.

SQL Querying

SQL Server and MySQL (joins, set operators, sub-queries, table expressions, data aggregating, pivot and unpivot

Data Visualization

Tableau 10 and R (ggplot2)

R Programming

Data manipulation, Data Modeling, Using Stats packages and Building Machine Learning Models using R Studio

Statistical Analysis and Machine Learning

Regression (Linear and Logistic), Classification (K-NN), Decision Trees, Clustering (Hierarchical & K-Means), Random Forests, and Time Series, NLP/Text Analytics, CART, Cluster Analysis, Correlations.

Advance SAS & SAS Enterprise Guide


OS Environments

Windows, Linux, and Amazon Web Services (AWS)

Web Technologies

HTML, CSS, XML, Bootstrap, and MySQL/PHP, Google Analytics


Certified Base Programmer for SAS 9

The Analytics Edge - Certified Course from

Google Analytics Certification


Crime Prediction Using Public Transportation Data and the Random Forest Algorithm, P. Zhao, N. Kapoor, M. Thakur, T. Ty, E. Moskal, G. Michaelson, S. Jaume, International Journal of Decision Science, Vol. 7, No 1, June 2016.


M.S. in Information Technology, Wilmington University, DE GPA 3.73 (Aug 2017)

M.S. in Data Science, Saint Peter’s University, Jersey City, NJ GPA 3.83 (Dec 2015)

MBA in Retail Management, IGNOU, New Delhi, India GPA 3.80 (June 2013)

Bachelor of Commerce, Loyola Academy Hyderabad, India GPA 3.98 (May 2011)


Customer Churn (switching carrier) Analysis for a wireless telecommunications company

Data consisted of 8,000 current and prior customers of which 22% were churned.

Using R fitted logistic regression model to analyze and select best predictor variables out of the four available variables: age, marital status, duration as a customer, and churned contacts count.

Orange Juice Blending Linear Optimization Model using Microsoft Excel Solver

Built a model to replicate Coke’s Orange Juice blending algorithm. Objective to minimize procurement cost while meeting all the specs of the product in terms of supply, demand and quality constraints (color and taste).

Machine Learning algorithm for identification of poisonous mushrooms using UC Irvine dataset

Implemented an algorithm to identify mushrooms by physical appearance and segregate poisonous mushroom from the mixed sample.

Base model achieved accuracy of 98.53% and advanced model achieved an accuracy of 100%.

Data Visualization (Tableau and ggplot2)

Startups Quadrant of High Growth Profitable companies - Dynamic dashboard with selection of cutoff values for Revenue and Expenses and selection for number of high growth companies

Citi bike NYC bike usage pattern study

World Demographics Animation (Life Expectancy vs. Fertility Rates)

Movie Rating Visualization and Chicago City Motor Vehicle Theft Visual Analysis

Term Project - Developing a portfolio web page

Used HTML, CSS and other web technologies.


Graduate Assistant, Dept. of Data Science, Saint Peter’s University, NJ Sep 2015 – Dec 2015

Collaborated with Data Robot Inc. to analyze data, and perform predictive modeling for crime prediction model for Bogota project.

Mentored new graduate students and conducted boot camps for R and Tableau.

Explored data visualization/mapping tools i.e. QGIS, and Carto DB for geospatial analysis.

Assistant Store Manager, Madura Fashion & Lifestyle, Bangalore, India Jun 2013 – Jun 2014

Oversaw and implemented overall store administration effectively by managing employees and store finances.

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