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Customer Service Sales

Campbell, California, United States
September 19, 2018

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Dipendra Shrestha

Campbell, California 650-***-****


California State University East Bay, Hayward, CA Graduated 2017

M.S. in Business Analytics, GPA: 3.85

San Jose State University, San Jose, CA Graduated 2015 B.S. in Applied Mathematics

Summary of Skills

Natural Language: English, Nepali and Hindi

Programming Language: R, SQL, Python

Development Tools: R-Studio, Atom, MS-Excel, MS SQL Server Management Studio, Tableau

Work Experience

People Shores May 2018-Ongoing

Process Associate

Installed Automation Anywhere software with its dependencies on 5 client machines

Developed login-bot that logs into Invoicely application

Developed bot that generates report based on report criteria provided on Excel file

Developed log-out bot that logs out of the Invoicely application

Varsity, Inc. Feb 2017-Ongoing Math Tutor

Handle skill-based tutoring in Algebra I and II, Geometry, Trig, Pre-Calc and Statistics

Develop resources to tutor students to build Math Skills

Evaluate students to measure skill progression and determine improvement areas

Nordstrom, Palo Alto, CA Sep 2007 - Dec2016 Sales Associate

Prepared sales action plans and strategies to target $10,000/ 2 week

Helped Nordstrom maintain sales pipeline by collecting/editing customer information

Recommend changes in product and service

Resolved customer complaints by investigating problems & developing solutions

Provided excellent customer service to all current and future customers

Educated customers and co-workers by answering their questions in detail as required

Pacesetter: A recognition for accomplishing yearly sales volume

All Star: A recognition for providing consistent extraordinary customer service


Automation Anywhere Certified: Advanced RPA Professional July 2018

Expandability Certified: Data Analyst Training Dec 2017

Machine Learning Project

California State University East Bay, Hayward, CA

Sentiment Analysis of Arabic Tweets June 2017

Imported the whole dataset into Excel and randomized the tweets to classify as ‘Positive’ and ‘Negative’ randomly mixed

Created training and test dataset with stratified sampling to guarantee random partitions with same proportions of each class in both sets of data

Applied Naïve Bayes algorithm to develop a statistical model and evaluated the model performance with accuracy of 73%

Medical Expense Prediction Jan 2017

Conducted an exploratory data analysis on data set to get information about the underlying trend and relationships between variables

Deployed AIC criterion to find out the best additive model without interaction terms

Performed normality test with the help of Q-Q plot and Shapiro-Wilk test which the model failed to justify

Chose coefficient of determination of 86% and equal variance which gave more reliable results while hypothesis testing

Breast Cancer Classification Sep 2016

Conducted Exploratory Data Analysis on the data set to shine some light on the relationships among the variables

Created a normalize function in R to normalize some numerical data to deploy k-NN algorithm which is heavily dependent upon the measurement scale of the input features

Created a training data set to build the k-NN model and a test dataset to be used to estimate the predictive accuracy of the model

Evaluated the model performance at 98% accuracy

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