Data, analytics and modeling executive with 25+ years in financial services (PNC, Freddie Mac, Capital One, ADB). Expertise in applying analytics and modeling to address business problems; in developing/executing data strategy and data governance; and in leveraging data, technology and process execution to operationalize solutions. Adept at leading diverse, cross-functional teams spanning business and technology. UC Berkeley Finance PhD with additional quantitative training that spans statistics (MS from Stanford), engineering, machine learning and data. Seeking to advance career around data science after recent full-time, hands-on experience at a top rated data science bootcamp.
SKILLS
● Risk analytics – portfolio risk measurement, loss reserving, economic capital and risk adjusted profitability, capital adequacy, risk-return optimization, consumer credit modeling, credit tranche valuation in securitizations
● Modeling and analytic solutions operationalization – data strategy, data governance, IT systems development, business process development, analytic process execution
● Programming languages and tools – Python, R, SQL, GitHub, Docker
● Machine learning – Supervised: Linear/logistic/penalized regression, decision trees, random forest, gradient boosting, SVM, discriminant analysis; Unsupervised: Clustering, dimensionality reduction
● People leadership – empowers and motivates team to put out their best, strong relationship builder, excellent communicator, sets vision and strategy while also in the trenches
NYC Data Science Academy’s mission is to provide accelerated data science training programs that prepare people for employment as data science professionals and to offer continuing education courses for professional development.
