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Data Analyst Assistant

Harrison, NJ
October 15, 2019

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Niharika Shetty +1-862-***-****


Rutgers University, New Jersey — Master’s in Information Technology & Analytics (Dec 2019) GPA: 3.66

Mumbai University, Maharashtra — Bachelor’s in Computer Engineering (May 2018) GPA: 3.68


Python, R Programming, SQL, Java, Algorithms and Data Structures, Machine Learning, DBMS, Tableau, MS Office, MySQL, SQL Server. Google AdWords, JavaScript, PHP, HTML, XML, C, SPARK, Flask, Hive, Seaborn, Mathplotlib, ggplot, AWS.


Google Analytics, AWS Cloud Practitioner Certification.


Data Analyst Intern – WISE (Jun 2019 – Sept 2019)

Extracting meaning from data and creating dashboards

Assist in utilizing data to create cases to develop product sales (25%)

Developed use cases for software development.

Work with the founder to interpret datasets to assist with the business decisions.

Analyzed business requirements and provided end to end solution design for data foundation builds including Data Marts, Data Feeds, Data Warehouse, etc.

Provide input into the development of a strategic plan for the fundraising campaigns, including fundraising goals, budget recommendations, vendors, volunteer goals, timelines and Evaluate the effectiveness of the on-going fundraising campaigns, including fundraising efficiency (cost/expense).

Managing Google AdWords account and developing a strategy for effective use of Google AdWords Grant, Pay Per Click advertising and Search Engine Optimization.

Participate in the development of marketing and Donor materials for both potential and existing Donors.

Program Assistant – Rutgers University (Dec 2018 – Jul 2019)

Extracted tutoring data and materials from Wufoo and entered information into tracking spreadsheets, documents and databases.

Created a database to store complex tutoring request data generated from versatile forms attributing to different departments of the university.

Created a Flask API using Python and SQL which collects data from the Wufoo forms and stores them in the SQL DB

Built collection, analysis and reporting frameworks from scratch and devised techniques for maximizing the usefulness of the system.

Built a dashboard using Tableau to display grades, performances, efficiency, counts of the students using the services with graphical displays and visuals for easy analysis.

Analyzed product and market to evaluate competitive market strategies and made actionable recommendations based on data trends.

Developed databases, web forms and file systems to fill different needs.


Credit Card Fraud Detection

Predicted fraudulent transactions for a European Bank using Python. The prediction models were built using ensemble methods such as Random Forests, Decision tree, ADA Boost and XG Boost. Oversampled the training data using SMOTE to over sample the fraud transactions. Random Forest yielded the highest accuracy with 0.94 AUC.

Pneumonia X-ray Classification

Built a convolutional neural network model to classify pneumonia based on patient x-rays. Classification was done on the basis of distinct features pertaining to positive and negative cases. It considers several x-rays of bacterial and viral pneumonia patients along with normal patients. It uses SoftMax to get the probability of the labels to work with the optimizer. Cross entropy is used as the cost function that can be used to guide the optimization of the result.

Hotel Management System

Developed a website for a Hotel and established a database connection with the website using HTML and Python. Produced MySQL queries for querying data against different databases

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