Data Analyst

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ANKUR BHAGWAT

*************@*****.*** +1-510-***-**** Hayward, CA linkedin.com/in/ankur-bhagwat/ Tableau EXPERIENCE

Data Analyst, California State University, East Bay Aug 2019 - May 2020 Compared 63 different metrics of 18 Cal State campuses & performed statistical analysis to analyze structured/unstructured sustainability-related data.

Built visualization dashboards & presented monthly data findings to the Campus Sustainability Committee to help them develop strategies & reduce operation costs.

Strategized & developed solutions improving the campus climate action plan and thereby reducing carbon emissions by 11%. Analyzed pilot printer survey data and proposed a solution of using networked printers instead of desktop printers thereby minimizing the cost spent on printers by $72,000 annually. Data Analyst Intern, California State University, East Bay May 2019 - Aug 2019 Designed a survey questionnaire in Qualtrics to accurately measure the opinions, experiences & behaviors of students on- campus.

Collaborated with StopWaste Alameda county & contributed in collecting, organizing & interpreting University’s food- wastage data. Further analyzed the metrics, to gain insights from the data.

• Delivered the findings to upper-management and developed strategies that reduced food wasted on-campus by 50%. PROJECTS

Severity Classification of Diabetic Retinopathy

Identified and classified retina images in one of the 5 diabetic retinopathy categories using various deep learning architectures. Built end to end CNN model with 11 hidden layers with a validation accuracy of 6 3% being 2X superior to the statistical approach.

• Performed fine-tuning on VGG19 architecture using the pre-trained ImageNet weights & improved the accuracy by 19% Credit Card Defaulters Identification

Led a team of 5 members that analyzed credit card payment data of a Taiwanese Banking Institution to predict and classify the customers into defaulters and non-defaulters.

Deployed various data mining methods such as Logistic Regression, Boosted Tree, Bootstrap Forest, Neural Network, K-NN and Decision Tree analysis for predicting credit card defaulters with an overall accuracy of 82% Anomaly Classification of Agricultural field images Developed deep learning model to accurately classify the anomalies in one of the six classes to improve the yield of the crops Achieved highest validation accuracy of 83% using inception V3 (Transfer Learning) Model Marketing Campaign Effectiveness

Implemented Decision Tree (Decision under uncertainty) in Excel and found an optimized marketing strategy with profit returns maximized by 21%

Used Various Visualization graphs such as Risk Analysis, Sensitivity Analysis, and Tornado graph to analyze the solution Web Data Scraping using Python

Utilized Beautiful Soup to scrape the data from multiple job listing websites, to help automate repetitive job listing keywords for analyzing the requirements, location, timeframe of a particular job posting Compared various job posting & created dynamic dashboards using Tableau to derive meaningful insights from the scraped data Database Foundations for Business Analytics

Created a physical database in MySQL, populated it fully with the college of business and economics data and normalized to 3NF

• Designed an Enhanced E-R diagram for the existing database & executed SQL queries to extract required information EDUCATION

Master of Science, Business Analytics Aug 2018 - May 2020 California State University, East Bay GPA: 3.625

Bachelor of Engineering, Electrical and Electronics Engineering Aug 2013 - May 2017 University Of Mumbai GPA: 3.5

SKILLS

Programming: Python, R, SQL, Hadoop, SAS, NoSQL

Visualization Tools: Tableau, Microsoft Power BI, Microsoft Excel, Qualtrics Soft Skills: Excellent Communication skills, Attention to detail, Teamwork, Problem-solving Technology/IDE & Tools: JMP, RStudio, Spyder, Google Colab, Jupyter Notebook Data Science/Big Data: NumPy, Pandas, scikit-learn, Tensorflow, Keras, Seaborn, MapReduce, Pig, HBase, Spark Machine Learning: Regression, k-NN, Random forest, Boosted trees, Bootstrap forest, Clustering, Association rules

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