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Data scientist

Cincinnati, OH
December 30, 2018

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Nitesh Agarwal

**** ********* ******, **********, **** 45220 ■ 513-***-**** ■ EDUCATION

University of Cincinnati, Carl H. Lindner College of Business, Cincinnati, Ohio Expected May 2019 Master of Science in Business Analytics

Vellore Institute of technology, VIT University, Vellore, Tamil Nadu, India May 2013 Bachelor of Engineering, Electronics and Electrical (EEE) GPA: 4.0/4.0 SKILLS & CERTIFICATIONS

• Industries: Retail & Automobile

• Technical Skills: R, Python, Tableau, SQL, SAS, Hadoop (Hive, Spark, etc.)

• Analytical Skills: Machine Learning, Linear Regression, Logistic Regression, Hierarchical and Non-Hierarchical clustering, Conjoint Analysis, Predictive Modeling, Support Vector Machine, Random Forest

• Certifications: Machine Learning by Andrew Ng – Stanford University (Coursera) – In progress Analytics Professional Experience

Aujas Networks, Bangalore, India June 2015 - April 2018 Consultant

• Created key performance indicators to identify potential fraudulent operators based on enrollment patterns for World’s largest biometric project

• Utilized Support Vector Machine Model to reduce the number of false positives by around 3% and assessed the feedback from the field investigation

• With this framework, the Government of India blacklisted more than 5k operators until now preventing potentially 200k fraudulent enrolment, amounting to a whopping Rs.115 million Affine analytics, Bangalore, India August 2014 - May 2015 Senior Business Analyst

• Dwelled deep into the U.S. car market to draw critical business insights and implemented the same while pricing the new cars for Sonic automotive in the U.S.

• Used Conjoint Analysis to automate the process of pricing new cars, which helps the client to price the cars and react to the frequently changing market scenarios

Mu Sigma Business Solutions, Bangalore, India May 2013 - July 2014 Trainee Decision Scientist

• Front-Line Optimization- Leveraged Segmentation Analysis to arrive at the optimal number of check-out counters to be active based on the customer flow and queue length in the Walmart store at a given point in time

• Reduced the average wait time of customers in client stores by 82% and resource wastage in client store by 7% HONORS & ACTIVITIES

• High performance award-Mu Sigma’s Cisco Walmart Project – 2014

• 1st Prize- Hackathon analytics competition, Affine analytics-2015

• Employee of the month, Affine analytics- Jan 2015

• Employee of the Year- Operator Scoring, Government of India Project- 2016

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