Director, Analytic Solutions - Sr. Scientist
CurrentFunctioning as Senior Scientist, I lead a 15-member cross-functional team focused on Automation and Operational RnD. Following agile methodologies and within an over-arching MLOps framework, we develop and deploy comprehensive automation architectures. These meld machine learning and other algorithm deployments with comprehensive monitoring, scenario-based forecasting, and simulation capabilities to develop complete solutions for operational task-replacement and associated R&D. My duties involve overall team leadership, mentoring, strategy development, operational planning and tracking, and C-suite communications. As a hands-on leader, I also make significant scientific SME contributions in the following areas: (1) development of ML models (xgboost, light gbm, MARS, random forests, elastic nets, statistical clustering), (2) applied statistics and demography, (linear and generalized linear models, including hierarchical models, demographic analysis and projections including mortality models, time-series modeling & forecasting, survival analysis (proportional hazards, AFT), (3) operational R&D (decision trees & probabilistic risk and decision analysis, system dynamics, computational simulation, optimization, queueing models), (4) deep-dive R&D focused on insights analysis, ongoing risk monitoring, ML model evaluations, and monitoring of bias & potential proxy discrimination in ML and other algorithmic models, and (5) behavioral science & epidemiologic research. Software utilized on a day-to-day basis comprise a modern tech-stack including: (1) scripting languages & associated IDEs: R (Rstudio, Posit Cloud), Python (Jupyter Labs, AWS Sagemaker, Sagemaker Studio), (2) GitHub for collaboration and documentation, (3) AWS for model deployment, (3) Dremio for universal data access and management using SQL, (4) mapping & GIS systems including QGIS, Arc-GIS Explorer, and Google Earth Pro, and (5) PowerBI & Markdown reports for monitoring purposes.