Sign in

Data Science enthusiast

Chennai, Tamil Nadu, India
50K- 80K
October 16, 2020

Contact this candidate


Vibeesh Kamalakannan


Phone: +91-755*******

Linkedin: Kaggle: Github: SUMMARY

I am an engineer with a passion for Data Science. I have professional experience in gathering, organizing, analyzing data, and developing machine learning models to make predictions. I'm looking for full-time opportunities where I can utilize my strengths in Data Science to make a positive impact on the organization as a whole. EDUCATION

B.E in Electronics and Communication Engineering

S.S.N College of Engineering • Chennai, Tamil Nadu, India • 2020 High School

A.M.M School • Chennai, Tamil Nadu, India • 2016


Data Science Intern September 2020 to Present, Los Angeles, California, U.S.A Katch Media

- Collaborated with analysts, developers, and product managers.

- Predictive modeling with NLP algorithms.

ML Engineer July 2020 - October 2020, Dallas, Texas, U.S.A Superior Data Science

- Utilized algorithmic and programming tools to build helpful predictive models.

- Deployed Machine Learning and Deep learning projects into production with Kubeflow. Data Analyst / Marketing intern July 2020 - October 2020, New Delhi, Delhi, India Guerilla Gaming

- Contributed to growth by improving customer database through web scraping.

- Reached target audience and improved the traffic coming to the events organized. Data Analyst Intern March 2020 - May 2020, Chennai, Tamil Nadu, India Konexxa

- Web scraping of products using Python (BeautifulSoup).

- Data Visualization using Python and Tableau.

Android Developer Intern November 2019 - January 2020, Chennai, Tamil Nadu, India KasponTech

- Developed various mobile applications using JAVA and MySQL. INDIVIDUAL PROJECTS


A program that takes in text, audio, or image input and gives a list of the items along with the quantity and the unit in a CSV format as output.



The algorithm greets you and answers questions about global warming using Natural Language Processing. Link:

Twitter US Airline Sentiment (Using ULMiT)

Sentiment analysis of the problems of major U.S. airlines. Data was scraped from Twitter. ULMFiT model was used to predict whether the text written by the client was positive, negative or neutral. Link: Smart Theatre

Augmented Reality is used to augment subtitles when the movie is played. This is currently built for android with future plans for AR Glass.

Long-short strategy for equity trading

50 Stocks from the SNP500 (during the years 2017-18) were analyzed. The data was scraped from Wikipedia and was ranked based on the computed log returns. After ranking, the top 5 performing stocks were selected to long and the bottom 5 were selected to short. This way, the portfolio can be rebalanced everyday effectively. Link: SKILLS

Contact this candidate