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Vinay Babu K J

@vinaybabukj

Data Scientist

Bangalore, Karnataka

https://github.com/Vinaybabu89

InnodataticsST. Joseph High School

Vinay is a curiosity-driven data scientist skilled in leveraging machine learning and data analytics to extract meaningful insights and solve complex business problems. He possesses strong analytical and logical thinking skills, aiming to contribute to organizational growth through continuous learning and teamwork.

Experience

Data science intern

Innodatatics

Internship•Jun 2020 - Mar 2021•Bengaluru

Data wrangling, Feature engineering, Data visualization to get insights from the data doing EDA using Tableau, Python matplotlib and seaborn, R studio libraries. Model building using various machine learning algorithms i.e. Supervised and Unsupervised algorithms. Evaluation and analysis of insurance claims dataset using Excel V-lookup, Chi-square, Normal and T-distribution. Removed outliers using Python and Pandas. Worked on scraping required data from various websites using Python BeautifulSoup, Selenium. Worked on deployment of ml models using Python Flask framework on various cloud such as Heroku.

Business

Vinayaka private LTD.

Job•Feb 2015 - Mar 2020•Mysore, Karnataka

Assistances and oversight for construction projects. Collaborated with development team. Allocated resources to ensure high performances. Researched, planned, crafted for business plans.

TEST ENGINER

SCA

Job•Jun 2012 - Dec 2014•Mysore, Karnataka

Quality testing under litmus tool. Test cases and execution.

Education

NIE Institute of Technology (VTU)

Bachelors Of Engineering

Information Science

Jan 2006 - Jan 2012•Grade: 59.66%

Maharaja PU College

PCME

Jan 2004 - Jan 2006•Grade: 57.70%

ST. Joseph High School

Jan 2004•Grade: 56.28%

Licenses & Certifications

Certification in completion of Internship projects

Innodatatics Inc

Issued: Jun 2020•Expires: Jun 2021

Data Science course

ExcelR Solutions

Issued: Feb 2020•Expires: Jun 2020

Skills

Statistical Analysis
Hypothesis Testing
Confidence Interval
Probability theory
Normal Distribution
Random Variable
Central Limit Theorem
Supervised Machine Learning (Regression, Classification, Survival Analysis)
Ensemble Methods (Bagging, Boosting)
Unsupervised Machine Learning (Clustering, PCA, Association Rules, Recommendatio
Text Mining (Text Processing, Tokenization, Stemming, Lemmatization, Sentiment A
Data visualization (Tableau, Forecasts, Tables, Charts, Dash Boards)
Regularization (Ridge, Lasso, Elastic Net Regression)
Imbalanced Data (K Fold Cross Validation, Data Partion)
Python (NumPy, Pandas, Scikit-Learn, Stats models, Matplotlib, Seaborn, SciPy, S
MY SQL
MS Word
MS Excel
MS Power point