Data Analyst Python MySQL, Excel, Tableau

Anurag Kumar ******.*****@*****.***

**** *. ***** **. **** #102, Tempe, AZ, 85281 206-***-**** linkedin.com/in/anurag-kumar Education

W. P. Carey School of Business at Arizona State University August 2019-May 2020 Master of Science in Business Analytics, 3.6 GPA Tempe, Arizona School of Electronics at KIIT University August 2012-May 2016 Bachelor of Technology, 4.0 GPA Bhubaneswar, Odisha Professional Qualifications

Data Mining MySQL Informatica PowerCenter BI

Tableau/Fast Analytics

Power BI

JIRA/User Stories

Microsoft Office Suite: Word, Advanced Excel,

PowerPoint.

Business Process Improvement – Lean and Six

Sigma Methodologies.

Python 3

Agile Methodologies/Scrum

Marketing Analytics

R Programming Language

Minitab

Software Development Lifecycle (SDLC)

SQL Services - SSIS/SSAS/SSRS

Text Mining/ Sentiment Analysis

Regression/ Predictive Analytics

Customer Relationship Management

Service Now

Information Lifecycle Management

(ILM)

Professional Experience

Data Research Scientist – First Source Analysis Jan 2020 - Present Arizona State University, Admission Services – Capstone Project Tempe, Arizona Analyzed data from several source including Salesforce and visualized trends from the past 6 years, going through almost 12 million admission records through Power BI and Tableau.

Analyzed bivariate associations between chronological first source and conversion rates followed by more comprehensive methods including first source sensitivity analyses and regression models. Developed a model with the Python using Machine Learning and Predictive Analytics – Multiple Regression and KNN models obtaining a low MSE, providing the client a better understanding of the impact of ASU’s organic sources, predicting what enrollment would look like.

Business Operations Analyst, Financial Services February 2017-July 2019 Accenture Solutions Private Limited Gurugram, Haryana Decommissioned 700+ bank legacy applications over 3 years, unlocking potential savings of up to £50M to the client. Used Agile Methodologies/Scrum in sync with JIRA/User Stories to track the progress and update requirements for the client’s competitive advantage.

Worked with a team of 8 - Six Sigma Green Belts and Black Belts to optimize the workflow using Service Now and Microsoft Office Suite for High Risk applications - gathered requirements from business and technical stakeholders, evaluated the current process and developed a solution by optimizing workflows/business process models. Awarded with Accenture Excellence Award – 2018 and Accenture Tech – Star Award 2019 for Client Management and Operations.

Data Analyst, Financial Services May 2016-February 2017 Accenture Solutions Private Limited Gurugram, India Archived 70+ legacy bank applications over various branches such as US, UK and Asia Pacific Designed mapplets, mappings and workflows for 50+ applications, by using Informatica PowerCenter BI tool. Automated entity mappings through manipulating MySQL queries for several Control Flows and Data Flows through SSIS and SSRS for 20+ complex legacy applications.

Used Information Lifecycle Management to perform Structured Data Mining data for 70+ legacy software applications. Improved application decommissioning rate by 15% by building predictive analytical models with MySQL and Python using Regression Analysis to identify application entities and workflows to be archived. Worked on Data Mining and Data Migration on ILM from DEV and UAT to PROD environments for 100+ applications. Academic Analytics Projects

Amazon e-Books Recommendation System - Developed a Recommendation System Model using Pearson correlation similarity measure and KNN clustering and Convolutional Neural Networks in Python to predict the e-book recommendation for the input user. Nike Customer Outreach Analytics - Used MySQL, Python - Sentiment Analysis, Tableau – Dashboard to determine what are the marketing strategies they should implement in accordance with their market thereby increasing 25% sales volume. Customer Satisfaction – Santander Bank - Used Python to train datasets for the best classification models for Santander’s customer base and predict potential churners to improve retention rate. Used Scikit-Learn and performed exploratory data analysis, hyperparameter tuning with cross-validation in Random Forest and Decision Tree classifiers and achieved 96% accuracy. (Data Mining/Machine Learning – Predictive Analytics – Kaggle Competition) Customer Churn Prediction Text Mining & Analytics - Applied relevant rules on the existing customer reviews to create new categorical variables for Good/Bad/Irrelevant reviews. Developed machine learning model to predict the number of Customers likely to churn using Ensemble method in Python and SPSS Statistics. With the help of stemmers with stop words, we constructed term-document matrix, TF-IDF matrix, compared Wrapper and Filter type feature selection classifiers and achieved 93.5% accuracy in Python’s NLTK.

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