• Having good Analytical, Mathematical and Statistical skills.
• Proficient in R and SAS.
• Proficient in SPSS.
• Hands on experience in statistical and modeling.
• Hands on experience in Linear Regression, Logistic Regression, Decision Tree, Random forest, XGboost and SVM.(Hands on experience is basically on projects).
• Hands on experience in unsupervised learning using K-means clustering and hierarchical clustering.
• Time Series analysis using - Hot winters, AR, MA and ARIMA.
• Data visualization in R using ggplot2 and plot for interactive graphs.
• Feature engineering in R and SAS. Missing value and outlier handling, Transforming variable, creating new variables, creating dummy variables, reshaping data using packages like dplyr and tidyr in R.