Principal Scientist Resume Lexington, MA - Hire IT People

SUMMARY

A senior computational scientist wif experience on working wif different statistical and predictive models on large and complex datasets in biology and chemistry.
Excellent hands - on experience in data organization, data processing and analysis, and data visualization wif experience working on numerous projects in a range of therapeutic areas.
Excellent scientific research, method and application development record wif extensive programming experience and ability to move ideas into new innovations; well published in teh area of computational science & informatics.
Successfully collaborated wif IT colleagues, scientists and management to develop and promote teh use of tools and technology to improve operational efficiency and more quickly progress discovery projects towards teh clinic.

TECHNICAL SKILLS

Python, C#/C++/C, Perl, Java, Matlab &R, SAS and SQL
Pipeline Pilot & KNIME, Spotfire, Dotmatics and Molecular modeling
Packages (MOE, Schrodinger suite, OpenEye package, etc.)
Computational modeling
Machine learning
Statistical analysis
Programming
Clustering/classification
Data mining
Large data set analysis
Data visualization
Similarity/diversity analysis

PROFESSIONAL EXPERIENCE

Confidential, Lexington, MA

TEMPPrincipal Scientist

Responsibilities:

Developed predictive antibacterial resistance and permeability models using a variety of machine learning techniques including random forests, Bayesian classification and TEMPprincipal component analysis. Deconvoluted generated models to identify good/bad chemical features in order to proactively guide teh design of prospective targets.
Analyzed HTS screening data for human disease project and provided teh follow-up support wfrom hits confirmation & concentration response to lead identification as well as series selections, included data mining from in-house and external structure databases - Using outcome from data analysis to make recommendation and decisions to support projects.
Worked closely wif project teams and members, providing proactive input, including suggestions of compounds to synthesize and identification of key compounds for in vitro/in vivo testing based on multiple dimensional data analysis results, profiling, series selection and advancement. Focusing on optimizing properties such as membrane penetration and resistance avoidance while maintaining target activity in order to improve MICs against difficult strains using linear and nonlinear models (data aggregation, descriptor selection, dimensional reduction and machine learning).
Designed project home pages and application tools to support project data retrieval, organization and visualization and SAR analysis.
Initiated a poly-pharmacology project targeting multiple ion channels for teh treatment of post-operative pain and led teh project through exploratory stages and follow-up working closely wif biology co-lead.

Confidential, Winston-Salem, NC

Senior Scientist

Responsibilities:

Developed linear and non-linear predictive models of Random Forest, Self-organizing Map, Partial Least Square and k-Nearest Neighbor for potential nicotinic a4b2, a3b4, a6* and a7 agonist/antagonist and channel modulator recognition.
Designed and implemented a novel diversity analysis method for high dimensional large data clustering, classification and visualization.
Utilized statistical methods to develop in-vitro/in-vivo translations used to identify source of both activity and adverse TEMPeffects and to better understand teh efficacy of nicotinic ligands in pain/smoking concession models, and provide support for selection process.
Develop tools for data analysis; R integration wif data visualization software; Regression Analysis/Predictive Modeling wif R
Initiated and automated web-based structure management and prediction site for medicinal chemists. This concept led to teh development of in-house automated data sharing system.
Developed and implemented a propriety Multiple Target Prediction module wif novel textual descriptors for use as routine predictions of various in-house assays as well as ADMET for all registered virtual structures and synthesized compounds.
Combined teh genetic algorithm, hill-climbing and simulated annealing wif pattern recognition methods to develop quantitative structure property relationship package for data analysis and model building.
Supervised contractors, post doctors and interns and provided support of postdoctoral grogram.

Confidential, Chapel Hill, NC

Research Associate

Responsibilities:

Developed and implemented modeling packages for library design, large multidimensional data diversity analysis, data mining and data mapping.
Collaborated wif Rohm and Haas’s computational chemists developing methodology for descriptor scaling and data analysis.
Developed ADME models using SAS package and installed them at GSK intranet for use as routine prediction tools for DNPK scientists.

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Principal Scientist Resume

Lexington, MA

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