Summary of profile and work Credentials. Data Analytics and Quantitative modeling Statistical Methods

1. Piyush Chopra Raychand
Chopra
716-431-9863
piychopra@gmail.com
https://www.linkedin.com/in/piyush-chopra-b93aa1105
Education
2015–2016 Master of Science, Industrial Engineering (Operations Research),University at Buffalo,SUNY, GPA 3.6/4.
2011–2015 Bachelor of Engineering, Anna University,Chennai,India. Mechanical Engineering, GPA 3.8/4.
Course topics
Stochastic Methods
Regression Modelling
Data Mining
Facilities Design
Supply Chain Engineering
Programming for Analytics
Time Series Analysis
Statistical Computing
Machine Learning
Quality Assurance
Linear Programming
DOE
Programming Skills
SQL
MS-Office
R
@Risk
SAS
C
Python
C++
Excel
SAS Visual
Analysis
MINITAB TABLEAU
Research Work
Spring 2016 Efficient Computation of Social Media Metrics using Text Mining Approaches.
• Developed Extensive documentation and reports on Performing Sentiment analysis, Topic Modelling, Analysis of Live-Stream of
data from Social Media websites and translated to a course on Social Media Analysis.
• Leveraged the use of R programming, SQL and Python to Scrape data from online platforms, Data Cleaning, Data Mining and
Visualization and applying machine learning methods – LDA, Logistic Regression.
Fall 2016 Probabilistic Modelling Belief propagation on Metabolic-Gene Networks of Alzheimer’s Disease.
• Undertook FBA (Linear Optimization) for gene-metabolic reconstruction networks and implementing Bayesian Statistics for Belief
Propagation and testing for Statistical Significance.
• Obtained large microarray datasets from Roswell Park Cancer Institute using data mining techniques to leverage descriptive
analysis using R programming and SQL for creating simplified clean datasets for further analysis.
Project Work
Fall 2016 Prediction of Bike-Sharing rentals at University at Buffalo using Multi-Variable Linear Regression.
• Worked with the Student body at University at Buffalo to predict the number of bike rentals on a daily basis.
• Performed data exploration, visualization and model building, applying machine learning techniques -R programming
• Applied Variable Selection (WOE and IV) and Feature engineering achieving 85 % model Prediction accuracy.
Spring 2016 Financial Credit Risk Modelling and determining Consumer behavior using Bayesian Network models.
• Devised a model leveraging the use of Bayesian Network Analysis and Greedy algorithms to classify the Credit Worthiness of the
customers and achieving a classification accuracy of 89%.
• Extended the use of statistical results into a business model by formulating a Cost-Profit Matrix to compare the accuracies of
Bayesian Model with Logistic regression and DA by giving higher penalty to False Positives.
Spring 2016 Smart Bidding strategy for simulated auctions using Python. .
• Built a code in python to simulate auctions periodically. Initially, random bids are placed for available auctions and profits are
calculated.
• Devised an optimized strategy using available history of winning auctions and the model was successful in outshining other groups
by winning high NPV bids, by a profit margin of 40k/1000and550/10000 auctions.
Fall 2015 Analysis of Airline Traffic Congestion using Time Series Analysis. .
• Extracted 20 years of Airline congestion data from Bureau of Transportation Statistics using SQL; data filtering, manipulation
and analysis done using R software.
• Fitted ARIMA, SARIMA and HoltWinters models and tested the model accuracy (ADF- Test, Values of RMSE, MAPE and
Sensitivity Analysis). Predicted the potential airlines which cause congestion at airports and estimation of their potential growth
for next 2 years.
Spring 2016 Modeling a Supply Chain Optimization Network for 3-echelon Supply Chains for Campus Dining..
• Formulated Linear mathematical models to minimize overall Supply-Chain cost using Gurobi-Python optimization, Descriptive
Analytics and Visualization using QGIS software on RAW Client data.
• Constrained Models to Selection of multiple warehouses, Aggregated Demands, Maximizing service levels, Transportation costs,
Multisite Sourcing and documenting the results for Port-Folio presentation and business decisions.
Fall 2015 Optimization of Foam Height from Root Beer using feature selection and classification. .
• Worked with a local brewery to find the optimal factor setting for the root beer dispenser.
• Regression and ANOVA to arrive at the optimal dispensing rate and performing feature selection. Developed process control and
capability charts to help in analysis.
Certifications/Trainings
Certified SAS BASE programmer
Getting and cleaning Data-John Hopkins University
Introduction to Data Analysis Using R- Big Data Univ
Certified Six Sigma Green Belt
Regression Models – John Hopkins University
Probabilistic Graphical Modelling – Stanford University

2. Professional Experience
Aug16-Dec16 Administrative Student Assistant at University Libraries.
Aug15-16 Student Assistant at Campus Dining and Services, University at Buffalo.
Nov14-Dec14 Administrative Intern at Khivraj Renault – Chennai.
• Worked with the Administrative front desk and shop floor to bridge the connections and shortcomings by simplification of
intermediate processes.
• Interacted with customers, performing portfolio analysis, managing inventories and improving customer service.
July14-Aug14 Process improvement intern at Faiveley Transport Rail Technologies - HOSUR PLANT.
• Undertook extensive case studies on Method-study and Time-study principles.
• Knowledge to the fundamentals of Process Planning, Quality Assurance and lean six sigma.