Profile: Senior level statistician/consultant with extensive experience in leading and supporting the effective use of structured problem solving, statistics, and quantitative methods t support technical and business decision making Designed and analyzed complex factorial experiments DOE used t develop new products and improve marketing decisions Worked as an internal consultant applying statistics and quantitative methods t support product improvement and development, manufacturing process improvement, development, and scale-up, and Monte Carl methods for financial decision making Developed and delivered internal training courses and workshops t marketing modelers, scientists, engineers, operators, technicians, and managers Received individual and team based awards for successful application of statistics t improve productivity and competitive position, and reduce costs Applied data mining and complex modeling methods t understand customer responses and build targeting models.

Technical Skills:

• Data Mining and Predictive Modeling: MARS, CART, Neural Nets, SVM, PLS
• Generalized Linear Models including Poisson, Logistic Regression simple and multinomial , Conditional Logistic Regression Matched Case-control and Discrete Choice models
• Multivariate techniques: Principal Component Analysis and Regression, PLS, Biplots
• Process Capability Analysis
• Univariate and multivariate SPC
• DOE: Design and analysis of efficient simple and complex nonorthogonal tw and multilevel factorial, response surface, mixture component, optimal designs
• Linear and nonlinear mixed model analysis including variance component estimation
• A priori sample size and power analysis used t ensure that experimental designs are cost effective and give meaningful results.
• Time series and forecasting analysis
• General Categorical Data Analysis
• Survival Analysis parametric and proportional hazards /Reliability Analysis
• Nonparametric analysis
• Robust modeling and missing data imputation
• Programming and deploying tailored statistical analyses using VBA for Excel, SPlus, and SAS JMP scripting Power and Sample Size Analysis, Compartmental Flow Nonlinear Models, Nonparametric Smoothing Applications, Tailored Components of Variance Application
• Develop and deliver training and workshops in statistics for scientists, engineers, non-degreed operators/technicians, managers
• Monte Carl simulation of financial models, nonstandard statistical analyses, and manufacturing models
• Bayesian multilevel regression analysis

Computing Skills:

• General Statistical Software: R, SAS JMP, Design Expert, Minitab, Log and StatExact, Simca P PCA and PLS , Crystal Ball, Risk, WinBUGS
• SAS UNIX, TSO, Windows,VMS : Base, Macro, STAT, IML, SQL Including Oracle pass-through , ETS, QC Optex, ADX and other design procedures including Kuhfeld Macros
• Programming: Matlab, Mathcad, MAPLE, VB, VBA, C

Employment History:

Confidential

Present: Senior Statistician,

Key Projects:

• Modeling of Audit Performance on 2 question categories t determine where training emphasis should be focused
• Unsupervised learning t detect patterns in respondents and questions: Distance measure based clustering and heat maps used t explore patterns in binary and ordinal responses along with block clustering methods t examine joint distribution patterns among questions and respondents.
• Supervised learning t predict performance vs. question type: PLS, SVM, and generalized linear model methods for binary and ordinal responses.
• Results: Successful implementation of training program that improved corporate audit performance by 25 in the first year of implementation.
• Modeling of Audit Question Effectiveness t reduce Audit Complexity
• Latent and manifest Item Response Theory methodology applied t model question discrimination and difficulty for binary logistic and ordinal cumulative link responses.
• Results: Reduced the number of questions by over 50 .
• Predictive modeling of raw material contaminants using NIR spectra as predictors
• PLS, Principal Components Regression, and Neural Net methods used t model concentration and presence-absence binary responses of key contaminants.
• Results: Successful implementation of cost effective program t detect raw material contaminants at production facilities and screen capability of suppliers.
• Support of new product design projects
• Employed Optimal Experimental Design methods and BIBs t develop efficient designs including mixture designs for modeling the effects of food attributes on consumer preference. Optimized food formulations using response surface methodology and optimization techniques such as desirability functions.
• Segmented experimental subject populations using probabilistic clustering with mixture models and fit separate models t each segment.
• Results: Most of the new products I have worked on made significant market share penetration at minimum development time and cost.
• Developed a Minitab training program t promote the effective use of data for understanding process variation.
• The training included graphical and numerical summaries, control charts, process capability analysis, and variance components.
• Results I have given the courses for over 5 years and the feedback has been excellent as indicated by the fact that I have been nominated for the annual Kellogg R D Coaching and Mentoring Award.
• Other Key Projects include:
• Measurement systems analysis as follow-up t process capability analysis
• Application of Multifactor Analysis, General Procrustes Analysis, and Multidimensional Scaling t analyze consumer projection maps and concomitant food descriptive and chemical data.

Sr. Marketing Information Consultant,

Duties/Experience:

Promote and support the effective use of experimental designs DOE in marketing studies. Mentor junior analysts on statistical methods. Developed predictive models from hundreds of potential predictors using data extracted from large ORACLE databases with SAS PROC SQL . In consultation with internal customers designed and analyzed mixed level 2 and higher factorial, fractional factorial, and custom optimal designs for market tests. Applied sample size and power analysis methods t ensure that the designs were cost effective and would produce meaningful results. Analyzed designs with OLS Regression or Logistic Regression Binary, Generalized, and Conditional logit models . Developed model based VBA simulation tools t predict scenarios based on future business strategies. Developed and delivered workshops t department members on efficient experimental design and power analysis. Developed VBA power and sample size application for Excel. Developed and delivered introductory and advanced courses in experimental design and power analysis. Advanced course in DOE included optimal design using SAS ADX, OPTEX, and Kuhfeld Macros.

Confidential

Duties/Experience:

Advised customers on the design and analysis of large factorial and custom optimal experimental designs. Employed time series and smoothing methodology t develop forecasting methods used t assess the quality of critical data base components. Consulted with internal customers on the analysis of primary market research studies.

Assistant Vice President

Confidential

Duties/Experience:

Promoted and supported the effective use of experimental designs DOE in marketing studies. Mentored junior analysts on statistical methods. Developed predictive models from hundreds of potential predictors using data extracted from large ORACLE databases with SAS PROC SQL . In consultation with internal customers designed and analyzed mixed level 2 and higher factorial, fractional factorial, and custom optimal designs for market tests. Applied sample size and power analysis methods t ensure that the designs were cost effective and would produce meaningful results. Analyzed designs with OLS Regression or Logistic Regression Binary, Generalized, and Conditional logit models . Developed model based VBA simulation tools t predict scenarios based on future business strategies. Developed and delivered workshops t department members on efficient experimental design and power analysis.

Senior Research Statistician

Confidential

Duties/Experience:

Provided expertise in statistics and structured problem solving t engineers, scientists, and managers engaged in research, development, and production efforts. Promoted and apply quantitative methods for business decisions and the efficient transfer of products from discovery/formulation t scale-up and ultimately t production. Developed simulation models for business processes and investment decisions. Developed and implemented statistical models t optimize production processes. Designed and analyzed Toxicology trials. Analyzed case-control and life-table data for epidemiology studies. Developed and taught courses t engineers, scientists, and managers in the following areas: Financial Model and Project Planning Simulation, Introductory Statistics, Mixture/Formulation Design and Analysis, Factorial and Fractional Factorial Designs, Response Surface Methodology, Components of Variance Gage R R , Control Charts, and Statistical Methods in Calibration. Consulted jointly with engineers on 6 Sigma projects. Developed statistical applications in EXCEL using VBA, Splus, and SAS JMP. Develop and deliver workshops on statistics using SAS, JMP, Design-Ease/Design-Expert, and Microsoft EXCEL for statistics and data analysis.

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Project Manager

Confidential

Duties:

Applied data mining and other analytical methods t analyze physician prescribing patterns t develop models used t optimize sales force allocation. Developed complex SAS code t extract and manipulate primary data from data sets comprising millions of records. Managed the quality and timeliness of recurring deliverable reports t sales force.

Senior Statistician, Confidential

Duties/Accomplishment:

Provided statistical expertise t scientists and engineers involved in product development and production. Developed and taught courses in experimental design and analysis and response surface methodology. Lead statistical effort in major process improvement effort at production facility. Through the use of experimental designs output efficiency increased 30 .

Confidential

Duties:

Assisted clinical research personnel in the design and analysis of clinical trials and provide other statistical support as needed. Wrote statistical sections of clinical reports and protocols.

Confidential

Duties:

Provided statistical expertise t research scientists. Wrote statistical sections of reports and grant applications.

Confidential

Conducted research on the ecology of marine organisms. Wrote proposals and papers, and presented results at meetings.