SUMMARY

Masters of Science in Information Technology Management from Oakland University in December 2017 with a 3.76 GPA

Professional experience as an SAP Intern at BorgWarner

Hands-on experience with the prevailing analytical tools/Skills: Tableau, Qlik Sense, PowerBI, SQLprogramming, R & Python, RDBMS includes MS Access, MySQL and MS SQL Server

EXPERIENCE

BorgWarner

IT analytics & SAP Intern Oct 2017 to Present

Implemented management level analytics dashboard to track SAP sensitive access and changes. This included gathering requirements, extracting and analyzing source data, designing, testing and launching dashboard to production ( Tools Used: Qlik Sense, SAP GRC Module)

Documenting EDI workflows to support global standards

Coordinate and maintain North America Batch job list in production

Perform SAP security maintenance including testing, defining and managing SAP user access according to audit policy

School of Business, Oakland University

IT Student assistant July 2016 to Nov 2017

Managed ticketing system by analyzing the root cause of the problem and provided with best possible technical solution immediately

Generated concise vision statements and organized a timeline for the planning process

Maintained databases, developed and implemented effective updates and utilization strategies

Developed key reports on the inventory release, vendor delivery, support and services details

TeleDNA Communications

Engineering Intern Dec 2014 to May 2015

Assisted in improving the Design of Wearable Wireless Knee Belt System which helps in capturing all the human gaits. Significantly reduced the cost of the system by 43%

Analyzed and generated reports of Captured the data for the use of physician to better assess the patient’s condition

Connected the system to an android application to quickly access the patient’s reports based on priority

PROJECTS

St. Joseph Mercy Oakland Hospitals

Clinical Data analysis Jan 2017 to May 2017

Worked with the Hospital staff to analyze the gathered and documented reporting requirements.

Streamlined more efficient data collection procedures and reconciliation of data obtained from a variety of sources (Power chart tool & SAP system)

Co-ordinated with doctors to understand the treatment process and validate the collected data, and ensure the variable selection for analysis

Conducted data analysis using logistical model, KNN, tree classification and random forest methods to identify key factors influencing the efficiency of treatment process and reduce the risk to patients by 30%

Presented reports on daily, weekly and monthly basis results to the management which helped in improvement of overall process by 56%

Visualized the results in Power BI and iDashboard which helps in identifying the key areas where process needs to be implemented

ACADEMIC PROJECT

Oakland University Masters of science in Information Technology Management Jan 2016 – May 2017

Project#1: Data Modeling and Data Mining – Microsoft SQL Server, PowerBI

Responsibilities:

Captured and documented business requirements for Data Warehouse System from the Travel Agent

Developed ETL application using SSIS packages to Extract, Load and Transform the data from Excel File into SQL server database using features like Lookups, Derived Column, Merge Join, Conditional Split, Union all, etc.

Formatted Drill-through and Drill-down reports using SSRS (MS SQL Server) to identify Price trends and analyze on-time performance of the airlines

Resulted data is visualized using PowerBI (multi-dimensional charts) which gives clear insights of the data to improve the customer satisfaction and provide ideas for business growth of travel agency

Project#2: MySQL Database application for an Enterprise – My SQL,Tableau

Responsibilities:

Analyzed business requirements from the Coffee shop owner to design an E-R Diagram and Data warehouse

Developed repeatable process for business owners to continually analyze and improve business operations

Predicted customers preference based on order history to maximize sales efficiency using logistic regression

Analyzed inventory usage reports to avoid backordering, Identified the products with high risk of loss and updated inventory which improved the profits of the coffee shop

Generated weekly and quarterly Metrics to track trends, changes in business climate, and statistical variances

Project#3: Statistical Analysis – Python & R, Algorithms

Responsibilities:

Modeled and imported large data sets from CSV files to SQLite3, then cleansed the data using Python

Computed aggregate statistics against the data using R functions: KNN, Decision Tress and Neural Networks

Plotted the results using the Python packages: ggplot, seaborn, MATPLOTLIB

Project#4: US Car sales Prediction – Excel VBA, SAS JMP

Responsibilities:

Researched and collected data for the historical input factors such as employment rate, Fuel price, location, mileage etc. which are influencing the US cars sales

Cleaned the data and Performed multiple linear regression analysis using SAS JMP tool to Predict future auto sales based

Designed macro-enabled User Interface workbook based on the Predicted results which allows the user to navigate thru various suggested reports on car sales, avg fuel cost per annum etc. based on the selection criteria of the user

EDUCATION

Master of Science in Information Technology Management Oakland University December 2017

GPA 3.76

Concentration in Business Analytics

Course Work: Software Project Management, Statistics for Managers, Big Data Analytics: Hadoop Pig, SPARK, HBase, Decision Support System, Operational Analytics

Bachelor of Engineering in Electronics and Communication Engineering VIT University June 2015

GPA 3.6

TECHNICAL SKILLS

Programming Languages: Python, Visual Basic, R Programming, Java, SQL Programming, MATLAB

Databases: Microsoft SQL server, MySQL, SQLite, MS Access, Oracle

Server tools: SSAS, SSRS, SSIS

Tools: SAS-JMP, Tableau, PowerBI, Qlik Sense, PowerPivot, XLMiner, Precision Tree, advanced Excel (VLOOKUPs, Pivot tables, Charts, Formulas-IF ELSE, Goal seek, Solver, Macros), Palisade Decision Tools (@Risk, @Precision Tree, @Neural Networks), Altreyx, SQL Server Management Studio, Business Intelligence Development studio.

Statistical analysis: Decision Analysis, Optimization, ANOVA, Linear and logistic Regression, Multivariate analysis, Hypothesis Testing, Time series modeling and analysis, Clustering analysis, Classification models, Regression trees, Neural Networks, Regression based Forecasting, Affinity Analysis, Simulation and Risk analysis

Big Data Technologies: Hadoop tools for data acquisition, MapReduce, Pig, Hive, and Impala

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