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Engineer Food Safety

Pittsburgh, Pennsylvania, United States
August 19, 2018

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Alekya Kumar


University at Buffalo, Buffalo NY 2017-2019(February)

Master of Science in Engineering Science (Data Science) Anna University, Chennai, India 2009-2013

Bachelor of Engineering in Electronics and Instrumentation Professional Experience

TATA Consultancy Services, Chennai, India 2013-2017 System Engineer - Analyst – a US Airline Major

Baggage Sortation Message (BSM) project

An automated system that helps in efficient sorting and delivery of bags in order to reduce the wait-time of passengers

• Liaised with the client to implement an automated baggage sort system to deliver bags to respective terminals

• Involved in end-to-end data analysis and deployment of BSM thereby reducing time for baggage delivery by 70%

Reservation System Migration

Migration of System from SABRE Global Distribution System to Altea Reservation System

• Carried out the pre-production validation for International Program during schedule load- ing and coordinated with SABRE team to ensure code is dropped to test system

• Designed a UNIX based tool for PNR confirmation and achieved 85% reduction in manual efforts necessary

Projects 2017-2018

Data Analytics: Food Inspection for city of Chicago, Illinois - Python and SQL Analysis of real-time data in order to study the inspections that promote public health in areas of food safety and sanitation and prevent the occurrence of food-borne diseases

• Analyzed and manipulated correlation and dependence of each variable towards another

• Estimated the maximum likelihood of a specific Facility Type according to the level of Risk, using Bayesian approach and predicted that there would be a risk of 65% Predictive Analytics: Wine Quality Data (Red and White) - R Predictive Science methodologies to assess the quality of two different types of wine using their chemical properties

• Explored the physico-chemical properties of wine and visualized the differences between white and red wines

• Studied the performance of KNN, Support Vector Machines and Random Forest;adjusted the parameters of Random Forest and achieved an accuracy of 94% Machine Learning : Multilayer Perceptron Neural Network - Handwritten Digits and Face Recognition - Python A supervised learning model implemented using Neural Networks to recognize handwritten digits and Celebrity Faces

• Implemented Forward Pass and Back Propagation algorithms for different combinations of hyper parameters and produced maximum accuracy of 90.2%

• Designed a Deep Learning model - Convoluted Neural Networks(CNN) using Tensorflow for recognizing celebrity faces;tuned the parameters and produced an accuracy of 97% Recommender System : On-line Dating Website - R, Spark and AWS A system that provides recommendation to users for a Dating website

• Conducted initial analysis on the dataset, containing 17 million records/ratings given by users, using Spark and AWS and understood the ratings provided by each user to a user- profile

• Devised an algorithm that uses ratings and similarities between users to recommend user- profiles.Produced a very low error of 2.6579 using Pearson Correlation methodology Contact





Python, R, SQL,


ITIL, Unix and Shell

Scripting, Java


Oracle, SAS Eminer,

RStudio, Jupyter

Notebook, Eclipse,

AWS, Tableau,






Regression, Neural

Networks, Decision

Trees, Clustering,


Systems, Time Series




ITIL Process, Agile

Methodologies, Client

and Team



•Statistical Data

Mining - Supervised

Learning and



•Probability Theory

•Predictive Analytics

•Object Oriented


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