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Engineering Data

Lafayette, Indiana, United States
October 21, 2016

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Email: Address: 402 Waterfront apt. 320 BrownSt. West Lafayette, IN-47906 Phone: 765-***-****

Education: Master of Science –Engineering Management (Analytics/Statistics), Purdue University Dec-2016(expected)

Member of NOBE (National Organization for Business and Engineering).

Applicable Course Study: Advanced Data Analytics, Marketing Management, Applied Regression Analysis, Engineering Economic Analysis (Game Theory), Information Engineering, Statistical Quality Control, Systems Simulation, Linear Programming, Accounting for Managers,, Strategic Management GPA-3.68/4

Bachelors of Technology-Chemical Engineering, Osmania University Sep2008-May2012; GPA-82% Achievement: 2nd prize – National Level Design contest - working model of ‘Desiccant wheel’, Bits Pilani, Goa campus.


‘Prediction of Credit Risk Customers’: Project deals with classification of customers as a credit risk or not based on the historical data of the customers and helps in making decision of future loan approval. The Data set consisting FICO score, Debt-to-Income Ratio, Request Amount, Interest Rate and loan approval variables (10000 customers) were analyzed using K-Nearest Neighbor Algorithm /Logistic Regression to classify the customers. Tools Used: SAS, R, Tableau Feb-2016

‘Prediction of Airline delays’: Project is to determine the best time to travel in order to minimize airline delays. Dataset consisting of 48,000 records collected from Bureau of Transportation Statistics, for American Airlines flights is used as the basis for analyzing the historical delays of flights and developing a predictive model to estimate the delay of a particular flight. Various Predictive Modelling Techniques such as GLM, GAMS, MARS, CARTS, Randomforest, SVM and NeuralNet were used along with 10 fold Cross validation to come up with the best model which gave the minimum Test Error and explained the Maximum variance in response variable. Tools Used: R, Tableau Mar-2016

Professional Experience:

WELLS FARGO – Enterprise Global Services (EGS), India

Senior Analyst: Jul2012-Jul2015

•Analyzed and evaluated large quantities of data in relational databases (Sybase, Oracle, MSSQL) effectively balancing quality, availability, and timeliness.

•Leveraged advanced data analysis skills and created innovative approaches to answer most relevant questions of clients across major trading hubs of the globe such as HONGKONG, US, LONDON and DUBLIN.

•Used SQL, Excel and VBA to report, monitor and generate data to address Ad hoc requests of operations Team.

•Analyzed and troubleshot various foreign exchange trading Applications by Debugging the Logs on Linux/Unix and Windows servers.

•Avoided manual effort by implementing Save Project-‘FX Rate Distribution Process Optimization’ Annualized effort gain of 69 hrs, equivalent to $1,517.


Achieving Excellence Award- Wells Fargo Dec-2014

"Best Practice Award Nomination", FX Application Team- Wells Fargo May-2014

Demonstrated Teaming: Received Shared Success award for striving towards shared Goals as a team, 5 times in 3 years of work experience at Wells Fargo. Jul2012-Jul2015

Key Skills: Business Intelligence/Data Analysis Tools: SAS, R-Programming, Minitab, Tableau Databases: MS Access, MSSQL, Sybase, Oracle, PL/SQL Programming: MS Excel Advanced, C, VBA, MATLAB Simulation software: AspenPlus, Arena Technical: Data structures, ANOVA, Design Of Experiments, Data mining, ETL, Machine Learning Concepts such as Principal Component Analysis, Cross Validation, Classification Techniques,Clustering, Segmentation, Association (Market Basket Analysis), Neural Networks, SVM, Decision Trees, RandomForest, GAMS

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