Head of Data Science Analysis, Financial Services
Dave is experienced in predictive analytics and statistical analysis using frequentist and Bayesian approaches. His specialty is in computationally intensive analyses due to large data size and/or complex methodology. Dave's statistical expertise includes experimental design, multivariate models, mixed models, GLMM, GAM, semi- and non-parametric models, correlated data analysis (repeated measures, time series, spatial statistics), CART, random forests, stochastic gradient boosting, rule ensembles.
Dave's past experience includes a wide swath of applied areas: accounting, financial, biology, chemistry, genetics, marketing, medicine. Some examples of my work include
- Insurance-specific frequency and severity analyses for loss development
- Financial statement fraud detection using innovative extensions of ensemble-based models
- Modeling of medical data
- Marketing analyses
- Innovative clinical trial design for FDA drug approval