•Solid academic history on machine learning, data mining and statistical models. Deep understanding on model building process such as feature extraction, avoid over-fitting and measure goodness-of-fit.•Deep knowledge on shrinkage regression, logistic regression, SVM, PCA and Bayesian methods.•Strong time-management skill for multiple tasks, work toward deadlines, detail oriented and highly organized.•Great problem solving techniques, active team participant and capable of working independently.•Quick learner (self-taught SQL, MATLAB) and self-motivated with passionate on new materials in related fields.•Good oral and written communication skills: experience with Powerpoint presentations and project reports.•Adept data processing and programming skills with R, SAS, MATLAB, Java and Python.
Listed skills include Statistical Data Analysis, Data Analysis, Sas Programming, R, and 11 others.