1. Prashanth Guntal
#77 Upper Dorset Street, Dublin
Phone: +353 894338640 Email: prashanth09071994@gmail.com
LinkedIn GitHub Website
PROFILE
Currently pursuing my graduate studies in Data & Computational Science at UCD, I have acquired
technical knowledge and skills from my course as well as practical and functional knowledge during
my 2.5 years’ work tenure at Intel. I am currently seeking a career in a data related role which will
enhance my passion for Problem Solving and puts me on a constant path of Personal and
Professional growth.
PROFESSIONAL EXPERIENCE
Dot Data Analyst Jan 2018 – Jul 2018
Intel
• Leveraged advanced analytical techniques to solve business problems from various Intel
IT departments and built interactive web-applications using R Shiny (R, R Shiny, ggplot2)
• Implemented regression models and decision tree algorithms to analyze and predict faulty
in manufacturing products up to 80% accuracy (Python, R, SQL)
• Developed python code to monitor the CW’s movement inside the office environment and
block their company owned mobile camera once they step inside the campus.
• Visualized various monthly dashboards of sale department using Tableau and performed
the knowledge transfer activities for many reports.
Automation Engineer Jan 2016 – Jul 2018
Intel
• Helped in saving 7 hours per day of a manual QA by automating use cases, test scenarios
for Intel customized Client applications (such as Adobe reader, UE-V, Foxit reader, Office
2016, Unite and Password Security Website) and few Intel in-house applications (App store
and Virtual assistance center). Worked in Agile methodology in delivering scripts.
• Solved the major issues currently faced by client UI automation teams by developing
automation scripts with Zero percent user interaction once the automation starts execution.
• Integrated image processing to automation framework to capture the image and convert
the image data into text which saved 3 days of manual QA time for testing the client/laptop
app which is used to share screen.
• Developed scripts to identify unauthorized access to different servers and users are
notified with respective message along with deadline and auto deletion of user account
from server after the deadline if no proper justification is provided.
• Trained my new fellow colleagues about automation framework built and particular coding
standards followed by team.
• Interacted with stakeholders from countries such as Ireland, USA, Malaysia and India
during my time with Intel as part of scrum team and received numerous appreciations along
the way.
PROFESSIONAL SKILLS
Technologies: Statistical Machine Learning, Financial Derivatives, Agile/Scrum Methodology, GIT
Programming Languages: C, R, C#, Mathematica, Python, H2O
Database: MySQL
Framework: Spec flow, White Framework (BDD), Selenium, NUnit.
Software: Visual Studio, Eclipse, Tableau, JIRA, Rally, ARINA, MS Office Applications.
2. EDUCATION
Master of Science in Data & Computational Science September 2018 – Present
University College Dublin 3.49 GPA
Bachelor of Engineering in Information Science August 2012 – May 2016
PES University 8.3/10 GPA
ACADEMIC PROJECTS
Title: - Sentimental Analysis on Amazon Product Reviews - UCD 2019
Brief Description: - Sentiment analysis was performed on big data (with 3 million reviews and
28 million words) from Amazon product reviews to classify the reviews into positive or
negative. ML models used: KNN, SVM, Gradient Boosting, Logistic Regression, Naïve Bayes
Multinomial, Naïve Bayes Bernoulli, Decision Tree, Generalized Linear model, Distributed
Random Forest, H2OAutoML.
Programming and Database: Python and MySQL.
Distributed Computing Engine: H2O.
Title: - Lower Back Pain Diagnosis using Various Classification Algorithms - UCD 2019
Brief Description: - Used the various Machine Learning algorithms like Random Forest, SVM,
Logistic Regression, Boosting and Bagging to classify the Lower Back Pain Data using R and wrote
a report on which among these classifiers was best suited for my analysis.
Title: - FIFA 18 Ultimate Team Prediction - UCD 2018
Brief Description: - Used the various concepts of Advanced Predictive Analytics to predict the
best squad based on overall rating of players across the world to form Ultimate dream team by
determining relationship between overall rating and other attributes of a player.
Title: - Analysis and Visualization of Fantasy Premier league (FPL) data -PESU 2015
Brief Description: - This project was developed with an aim of providing better understanding on
the Football player performance over the past week in the current league season in FPL (Fantasy
Premier league).
Web scrapping: Python, Library Beautiful Soup 4
Database and Visualization: MySQL, QlikView
AWARDS and Achievements
1. Received €4000 student scholarship from UCD.
2. Won 2nd place in Hackathon event conducted in Intel for developing IOT devices.
3. Received multiple recognitions for helping production support team by automating the
manual and time-consuming jobs.
OTHER INTERESTS
1. Following and Playing Cricket.
2. Actively following EPL (English Premier League).
REFERENCE:
To be provided upon request.
