Director, Modeling and Data Analytics Resume Thousand Oaks, CA - Hire IT People

SUMMARY:

Data Scientist experienced in developing, troubleshooting and deploying complex mathematical models of real world problems.
Highly skilled in the areas of computer simulation, data analysis, algorithmic and data modeling techniques with demonstrated applications to real life problems in diverse areas including health care, business, finance, and engineering.
Key technical contributor with creative multi - disciplinary approach and excellent analytical skills providing technical innovation and solutions to compute intensive problems.
Proven successful work history demonstrating ability to work independently or in team setting. ptimization techniques (linear / nonlinear optimization methods, multi-objective constrained optimization); machine learning / data mining (neural networks, clustering, SVM, Bayesian learning, deep learning), system identification and nonlinear parameter estimation; signal processing, compressive/sparse sampling, wavelet transforms/filtering, denoising, statistical data analysis; image processing, feature extraction, algorithm development for classification and recognition; modeling and analysis of longitudinal data, mixed effect models.

EXPERT LEVEL PROFICIENCY IN:

Programming Languages: C / C++, SQL, Python;

Software: Matlab, Simulink, R, Git, Docker;

Operating Systems: Linux, Windows

PROFESSIONAL EXPERIENCE:

Confidential, Thousand Oaks, CA

Director, Modeling and Data Analytics

Responsibilities:

Developed scalable machine learning / Bayesian learning solutions for clinical decision support system based on available electronic medical records (EMR).
Developed mixed effect statistical models, performed Monte-Carlo simulations for dose selection based on the preclinical study data.
Developed a compressive sampling algorithm for time series allowing a significant reduction of the volume of collected data.
Built image processing and feature extraction algorithms and software for three dimensional (3D) micro scale computer tomography (CT) scans
Created a data processing pipeline and prototype tool for feature extraction, object tracking and analysis of longitudinal X-ray image sets.
Performed statistical analysis and unsupervised learning of the longitudinal data sets containing unstructured data (extracted image features) using clustering.
Performed regression analysis of rapid affinity measurements of molecular interactions for high-throughput screening . Deployment of this platform allowed reduction of the total experimental time by more than 10-fold when compared to a standard approach saving company money and time.

Principal Information Systems Architect

Confidential

Responsibilities:

Developed a dynamical model and performed simulations of interaction of cell receptors
Developed a wavelet denoising method for Fourier Transform Mass Spectroscopy ( Confidential ) signals. The advantage of this approach is that it allows denoising without widening (degrading) the signal peaks, leading to more precise data analysis.
Designed and coded a range of web services for StarLIMS to extend and automate data analysis with additional regression models.

Lead Systems Informatics Analyst

Confidential

Responsibilities:

Developed a distributed model for the capacity planning project with the aim to predict the required resource to successfully complete a series of projects.
Analyzed resource allocation data for a capacity planning project that resulted in identification and elimination of resource bottlenecks.

Confidential

CAD Engineer

Responsibilities:

Developed and implemented effective algorithms for high order system identification and model order estimation based on maximum likelihood estimator.
Designed and implemented a computationally efficient constrained optimization algorithm that streamlined the process of shrinking die size, resulting in less cost per product sold.