Data Scientist / Quantitative Analyst
Resume:
MICHAEL YAMPOL
New York, NY *****
*******.******@*******.***
SUMMARY
Data Scientist and Quantitative Analyst with broad expertise in data analytics, risk methodologies and mathematical finance. Experienced in development and validation of analytical and statistical models. Skilled in understanding business goals, communicating results across audiences, distilling complex information, and extracting insights and utility from large data sets. Interested in Predictive Modeling, Artificial Intelligence, Machine Learning, NLP, Business Analytics, and Data Mining. Graduate degrees in both Statistics and Financial Mathematics; undergraduate degree from Harvard in Applied Mathematics. Completed Data Science Bootcamp and currently pursuing MSDS, incorporating extensive usage of Python, R, MySQL. EXPERIENCE
JPMORGAN CHASE, Brooklyn, NY 2019 – 2020
Vice President, PPNR/CCAR predictive model development
• Develop, test, and document forecasting models for prediction of Pre-Provision Net Revenue (PPNR) for Global Markets trading businesses under baseline and stress scenarios for Comprehensive Capital Analysis & Review (CCAR) exercise.
• Utilize time-series regression techniques such as OLS, SARIMA, and robust regression to forecast response of capital markets revenues to macroeconomic variable shocks under specified baseline and adverse scenarios.
• Using R, implement and optimize Machine Learning regression techniques such as Stepwise and Best-Subsets regression to select optimal predictive models based on statistical metrics such as adjusted-R2, AIC/BIC, RMSE, MAE, MAPE, etc. PRICE WATERHOUSE COOPERS (PwC) (contractor), New York, NY 2018 Stress Testing Model Validation Consultant engaged by PwC for CCAR model validation project at a major foreign bank.
• Subject Matter Expert responsible for validation of revenue projection and risk models for asset management business.
• Performed validation of Pre-Provision Net Revenue models for Active, Passive, and Alternative market segments.
• Reproduced client’s SAS-based regression model results and statistical tests using R code.
• Examined macroeconomic variable selection, transformation, stationarity, stability, robustness, autocorrelation, in-sample and out-of-sample performance, and measurement of forecast quality using standard model diagnostics. GOLDMAN SACHS (contractor), New York, NY 2017 – 2018 Quantitative expert engaged by IA Model Risk for annual Comprehensive Capital Analysis & Review exercise.
• Subject Matter Expert responsible for examining model development, governance, validation, and usage of Market Risk capital models.
• Performed detailed examination of Risk-Weighted Assets (RWA) projection models including Comprehensive Risk Measure, Incremental Risk Charge, Value at Risk, and Stressed Value at Risk for forecasting of capital requirements.
• Examined and tested developer code using Goldman’s proprietary “SecDB/Slang” environment. BANK OF AMERICA / MERRILL LYNCH, New York, NY 2009 – 2017 Multiple quantitative engagements as contractor/consultant from 2009-2015; converted to full-time employment in 2015. Senior Vice President/Senior Quantitative Finance Analyst for IA Model Risk, 2015 – 2017
• Subject Matter Expert responsible for examining model development, governance, validation, and usage of Global Markets pricing and risk models. Performed detailed examination of interest rate and counterparty (XVA) models.
• Examined and tested developer code under Bank of America’s python-based “Quartz” environment.
• Reviewed suitability, quality, and limitations of data utilized in model development and ongoing model use. Quantitative Analyst (contractor) for Counterparty Credit Risk Analytics model development team, 2014 – 2015
• Member of quantitative analytics team responsible for design of methodologies for counterparty risk models.
• Participated in development, testing, and rollout of multi-factor Cheyette interest rates and FX model used for projection of potential future exposure of counterparty risks under Bank of America’s python-based “Quartz” environment, leveraging parallel processing algorithms using Hadoop MapReduce architecture. Quantitative Risk Data Analyst (contractor) for “Big Data” risk aggregation project, 2012 – 2013
• Performed data analysis of Greeks and validation of derivative model results for Global Rates and Currencies desks. Quantitative Analyst (contractor) for Global Prime Brokerage Risk and Margin, 2009 – 2012
• Data Analysis expert for Strategic Margin Initiative, with detailed understanding of exchange-traded and OTC derivatives. Michael H. Yampol Page 2
CALYPSO TECHNOLOGY, INC., New York, NY 2009
Product Manager, Interest Rate Derivatives (Front Office)
• Analyzed quantitative requirements and created functional specifications for listed derivatives enhancement project. Senior Market Specialist, Pre-sales
• Prepared quantitative product demonstrations emphasizing Calypso’s Interest Rate and FX Derivatives functionality. LEHMAN BROTHERS, INC., New York, NY 2007 – 2008
Vice President & Senior Technical Lead, Emerging Markets / Foreign Exchange
• Designed and implemented analytics and technology for Latin American local currency trading desk using C++, Excel. CREDIT SUISSE SECURITIES (USA), LLC, New York, NY (formerly Credit Suisse First Boston) 2003 – 2007 Vice President, Risk Measurement and Management, 2006 – 2007
• Market Risk Manager / Quantitative Analyst for US Interest Rate Products and Foreign Exchange trading.
• Analyzed risks associated with US Interest Rate Derivatives, Treasury, Agency, Repo, and FX trading desks.
• Researched, recommended, and supervised implementation of enhancements to risk methodologies and technologies for calculation of Value at Risk and Economic Risk Capital.
• Performed stress-testing and scenario analysis to capture Risk Not in VaR. Vice President, Fixed Income and Credit Derivatives Technology, 2003-2006
• Designed and implemented web-based interest rate, credit, and emerging markets analytics using javascript and C++.
• Created and delivered “Financial Acumen Training Program”: taught software developers about bonds and derivatives. CERTIFICATIONS
GLOBAL ASSOCIATION OF RISK PROFESSIONALS (GARP), Jersey City, NJ
• Financial Risk Manager (FRM) certification, 2013 http://my.garp.org/DigitalBadgeFRM?id=50742 DATA SCIENCE DOJO, Redmond, WA
• Data Science and Data Engineering Bootcamp, 2017 http://verify.datasciencedojo.com/certificate/7ef05c2f EDUCATION
CUNY – SCHOOL OF PROFESSIONAL STUDIES, New York, NY 2018 – present Candidate for M.S. in Data Science (in progress):
• Advanced coursework in Statistics and Data Analytics, with intensive usage of R, Python, and MySQL.
• Program includes: Advanced Programming Techniques, Computational Mathematics, Statistics and Probability, Data Acquisition and Management, Business Analytics and Data Mining, Knowledge and Visual Analytics, Recommender Systems, Predictive Analytics, Machine Learning and Big Data. GPA: 4.0
• Academic Projects are viewable online at https://github.com/myampol and http://rpubs.com/myampol . CUNY – BERNARD M. BARUCH COLLEGE, New York, NY 2004 – 2007 M.S. in Statistics, 2007.
• Elected to Beta Gamma Sigma academic honor society. M.S. in Applied Mathematics for Finance, 2007 (program is now known as “Masters in Financial Engineering”).
• Joseph Ercolano Fellowship, awarded annually to the top graduate student(s) in Mathematics, 2005. HARVARD UNIVERSITY, Cambridge, Massachusetts
A.B. cum laude in Applied Mathematics/Computer Science. ANALYTICAL and TECHNICAL EXPERTISE
• R, RStudio, knitr, rmarkdown, tidyverse, caret, forecast, leaps, olsrr, ggplot2, mice, tm, glmnet, ranger, nnet, gbm, rpart
• Python, jupyter, numpy, scipy, pandas, scikit-learn, keras, TensorFlow, matplotlib, seaborn, plotly
• C, C++, MATLAB, Mathematica, STATA, SAS, Perl, Unix, Linux, Windows, Excel, VBA, Oracle, SQL
• Predictive Analytics, Data Visualization, Regression techniques (OLS, Logistic, Poisson, GLM, Lasso, Ridge, PCA)
• Machine Learning, Random Forest, Naïve Bayes, Neural Networks, Decision Trees, Gradient Boosting, SVM
• Econometrics, Time Series and Volatility Forecasting, Monte-Carlo Simulation, Historical Simulation
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