Shwitaan Sreenivas Ravikumar

720-***-**** adlcsg@r.postjobfree.com linkedin.com/in/shwitaan-ravikumar

TECHNICAL SKILLS

Certifications: AWS Certified Solutions Architect – Associate, AWS Certified Cloud Practitioner Data Analysis skills: Big Data Analysis, Machine Learning modelling, Data Mining, Data Visualization Languages: SQL, Python, R, SAS

Tools and Platforms: Microsoft Excel, Tableau, Power BI, Hadoop, Apache Spark, AWS, SAP HANA Databases: Microsoft SQL Server, Oracle, MongoDB

Python ML Packages: Scikit-Learn, Pandas, NumPy, Seaborn EDUCATION

The University of Texas at Dallas May 2021

M.S., Information Technology and Management

Anna University April 2017

B.E., Electrical and Electronics Engineering

BUSINESS EXPERIENCE

Global Electronics, Chennai, India August 2018 -April 2019 Business Analyst

Created visualization dashboards using Power BI to report the sales performance and thereby providing KPIs with respect to customers which helped the decision makers in forecasting the sales

Extracted the sales’ information from the Oracle Database using complex SQL queries

Developed new vendors through franchise distributors by analyzing the quarterly performance of the potential clients using pivot tables developed in MS Excel and procured contracts worth $160,000

Sourced electronic components from Original Equipment Manufacturers and Contract Equipment Manufacturers within 5 business days and assisted the logistics team in shipping the products KARS Metallurgical Marketing Ltd, Sharjah, UAE July 2017-July 2018 Business Analyst

Created 30+ Tableau dashboards with advanced functions to provide insightful analysis and identified key metrics to maximize profits that empowered the managers in decision making

Developed SQL queries to obtain the information regarding the sales from MS SQL Server database

Generated ad hoc reports containing pivot tables using MS Excel for analysis for the manager

Procured materials and lead a team of 10+ employees in logistics and warehouse operations ACADEMIC PROJECTS

Prediction of Employee Attrition October 2020

Designed a machine learning model to predict employee attrition using Scikit-Learn, NumPy and Pandas

The model is designed based on K nearest neighbour classifier, logistic regression, decision tree classifier, linear SVM classifier and kernel SVM classifier (Polynomial and RBF) algorithms

The performance is improved using ensemble learning techniques (bagging, random forest and boosting) Prediction of housing price October 2020

A machine learning model is designed to predict housing prices using linear regression, Polynomial regression, Regularized regressions (Ridge and Lasso), KNN regressor and Support Vector Regressor Big Data Analysis of Amazon Reviews February 2020 - April 2020

Analyzed the Amazon reviews in the AWS EMR environment using HDFS with MapReduce and Spark

The customer behavior is studied in detail and the trend analysis on the products is done with respect to product category, marketplace and year using PySpark and HiveQL

The findings were enhanced using Tableau visualization dashboards and Python libraries

The key metrics such as the sale of similar products in various categories is discovered whose inferences can be used to create Association rules and Collaborative filtering to improve the sale of the products Eligibility

Eligible to work in the U.S. for internships and for full-time employment for up to 36 months without sponsorship

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