PhD Experienced Statistician avaliable for Statistics Online Help

I am a professional statistician having PhD degree in statistics and faculty member at a university as well offering consulting services in the fields of statistics, probability, biostatistics, econometrics, optimization, actuarial methods and quantitative finance. I hold a PhD in Statistics (Reliability and quality Control 6 Sigma) with a minor in Management.

I help with academic study, independent study, dissertations, advanced research, big programming projects, business-related projects and data analysis in any of the major statistical packages (R, RStudio, Python, Matlab, Stata, SPSS, AMOS, EViews, SAS, JMP, Minitab, Excel). I work with all types of clients, from undergraduate students to full professors in other fields. The effective hourly rate depends on the level of material.

During my five years at the graduate school I taught more than ten undergraduate, master's level and PhD level probability and statistics courses. After graduation, for more than twelve years, I have been working in the industry focusing on projects in machine learning, time series analysis, Reliability and Quality Control 6 Sigma, QMS, data compression, computational statistics, stochastic optimization, pricing, quantitative trading and risk management. Equally importantly, I have tutored students and business professionals in all areas of statistics and quantitative finance for the last twelve years. I have consulted researchers in medical, social and economic sciences regarding statistical aspects of their research for fifteen years. Below is a list of selected past clients by type:

+ 150+ finance professionals,

+ 100+ MD, nurses and other medical professionals,

+ 80+ researchers in social sciences and marketing requesting help with the statistical part of their research,

+ 150+ doctoral students requesting help with their dissertation,

+ 250,000+ lines of code written in R, Python, Matlab, Stata and SAS for clients.

I will conclude with a more detailed list of the topics covered: non-parametrics, (nonlinear) regression, generalized linear models, MANCOVA, robust methods, longitudinal data, quantile regression, PCA, Bayesian inference, traditional Monte Carlo, MCMC, missing data imputation, time series analysis, econometric methods for large samples, random fields, data mining (boosting, random forest, deep learning, clustering, SVM, kernelization methods, bagging), meta analysis, stochastic calculus, renewal processes, survival analysis, reliability theory, investments & risk management, valuation of assets, prepayment models, corporate finance, actuarial modeling, numeric methods, classic and stochastic optimization.

Summary: college, graduate, post-graduate and business level consultant / tutor in probability, statistics, finance and actuarial science.