Experienced, hands - on Data Scientist with expertise in machine learning, deep learning and development of prediction models seeking data science / machine learning positions that fits with my passion for analysis of user behavior and prediction model development . Developed a recommendation system for libraries, based on customer usage of the e-books, and content of books, using MATLAB and solr. Applymachine learning techniques to analyze usage patterns for e-books. Analyzed and predicted the power usage of a large office building using time series analysis. Well versed in supervised learning techniques such as regression, ridge regression, clustering, decision trees and Bayesian statistics and ensemble methods. Possesses 15 years of numerical and mathematical modeling and data analysis.
CORE SKILLS INCLUDE:
Platforms: Windows, Linux
Tools: Matlab, R, SQL, Python, Java, Solr, PERL, Shell, MPI (Message Passing Interface)
PROFE SSIONAL EXPERIENCE:
Confidential, Mountain View, CA
Senior Machine Learning Engineer
- Developed a Patron Recommendation System for libraries based on usage and content of books.
- Similarity between books derived from complete content of the books indexed in Solr.
- Developed a suite of machine learning algorithms by analyzingthe contents of documents using Natural Language Processing.
- Utilize proficiency in Matlab, R and Python.
- Developed parallel and distributed algorithms in Matlab to analyze massive usage data sets.
- Used high performance computing to analyze one million text to find out similarity among documents.
- Analyzed user actions based on the clicks made by the user on the e-book reader to understand user experience.
- Develop inferences from the sales data, develop hypotheses and validate hypotheses using data.
- Perform mathematical and numerical modeling, time series analysis, data mining and machine learning with applications in engineering and oceanography.
- Applied unsupervised machine learning techniques such as Principal Componentand Independent Component Analyses for geophysical data.
- Supervise, mentor and guide scientists and engineers.
Confidential, Sunnyvale, CA
Consulting Machine Learning Engineer
- Performed data analysis of power consumption and development of models for power consumption.
- Developed statistical models using multiple linear and nonlinear regressions, Random Forests, and Seasonal Autoregressive Moving Average model to forecast power consumption.
- Developing statistical forecasting models in R.
Confidential, Palo Alto, CA
Engineering Research Associate
- Performed data analysis of oceanographic observations using multivariate statistical techniques, such as Principal Component Analysis and Independent Component Analysis, to find patterns in oceanic observations.
- Hypotheses developed from multivariate analyses were validated using dynamical model.
- Added C modules to an existing parallel coastal ocean simulator developed to model wind-driven circulation in San Francisco Bay.
- Used Python, Shell, and MATLAB scripts to run simulations in distributed computing using MPI (Message Passing Interface).
Confidential, South Kingston, RI
- Developed and applied mathematical and numerical models to simulate the movement of water in water bodies.
- Managed and supervised projects involving numerical simulations for solving engineering problems.