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Click here or scroll down to respond to this candidateCandidate's Name
Charlotte, NC Street Address
Phone: PHONE NUMBER AVAILABLEEmail: s tt rHighlights Street Address + years Model development, Validation and Implementation. 10+ years experience with SAS, R, SQL, Python, Machine Learning and statistical analysis. 10+ years of Big Data technologies (Hadoop/Py-Spark/Docker/kubernetes/NoSQL/TensorFlow/Kafka/Ni.) 10+ years experience in nancial sector (CCAR stress testing, credit risk and AML models). 5+ years experience with cloud computing platforms such as Azure, AWS, GCP. 10+ years of visualization tools Tableau, D3.js, Plotting (R Shiny, MatPlotLib, Bokeh) Education Ph.D. Computational Physical ChemistryState Univ of New York (SUNY), Buffalo, NY; Jan10 Dec14 M.S. Computational Chemistry/BioInformaticsUniversity of Connecticut(UConn), Storrs, CT ; Aug08 Dec09 B.Sc. Industrial EngineeringUniversity of Nairobi, Kenya; Oct01 May05, First Class Honors Work ExperienceVP, Sr. Quantitative Finance Analyst, Bank of America, Dec19Aug24 Performing all model validation tasks including but not limited to independent model validation, annual model review, ongoing monitoring report review, required action item review, and peer review. Communicating and working directly with relevant modeling teams and their corresponding Front Line Units; and if needed, communicating and interacting with the third line of defense (e.g. internal audit) as well as external regulators and governance agents. Build and implement the long term strategy for Machine Learning, including scoping use cases and practical examples of ML and AI wthin credit card space -both Acquisition and risk management ( targeting campaign, channels, collection and recoveries). Providing hands-on leadership for projects pertaining to machine learning approaches; fair lending; bias test- ing; Disparate Impact testing; and providing methodological, analytical, and technical support to effectively challenge and inuence the strategic direction and tactical approaches of these projects. Consultant: Data ScientistEmerging Data Tech, General Motors Financial, Arlington TX, Sept19Dec19 Evaluated, researched and experimented with computational learning technologies in a lab to keep pace with industry innovation while assessing business impact and viability to develope use cases. Explored Rasa, Spacy/Prodigy, NLTK, Standford CoreNLP, ELMo, and other natural language understand- ing and processing frameworks and other computational learning technologies such TensorFlow, Caffe, Torch, Neon, SystemML, Theano. Code, test, deploy, monitor, document and troubleshoot computational learning processing and associated automation. Assist in developing a RASA chatbot to be integrated with ServiceNow platform. Candidate's Name 2Sr. Quantitative Analytics Associate, Wells Fargo, Jul14Sept2019 Build clustering, classication and topic models for Anti-Money Laundering (AML) and Suspicious Activity Report (SAR) narratives using Machine learning concepts. As well as shepard the model through the various approval committees/ stakeholders across the organization (socialize the new models). Manage and analyze large, complex data sets using statistical tools and techniques (SAS, Python, R and SQL) Consider various machine learning algorithms/statistical techniques to reduce model errors and implement on AWS cloud. Monitor Model performance using a variety of metrics to support model annual review and re-validation. Perform model validations and documenting evidence of validation activities, while staying current with most recent quantitative and regulatory developments in the eld. Work on various ad hoc quantitative, modeling, and programming assignments Senior Model Analyst - CCAR models, M&T Bank, Buffalo NY, Dec13Aug14 Develop from scratch stress testing nancial models (for C&I portfolio) and lead the whole modeling process from beginning to end, beginning from input data cleaning, model selection to preparing model documen- tation for validation purposes. Monitor Model performance using a variety of metrics to support model annual review and re-validation. Build a AML model as part of high risk customer surveillance program AML/nancial crime analytics. Perform portfolio management campaign tracking and analysis as well as Identify opportunities to leverage statistical solutions to business problems. Examine conceptual soundness of models, challenge the underlying assumptions, theory, empirical evidence, limitations of the model as well as write validation reports. Extensive use of statistical procedures: PROC ANOVA, PROC CORR, PROC GLM, PROC LOGISTIC, PROC REG, PROC ARIMA, PROC MIXED, PROC TTEST and PROC UNIVARIATE. Performed scenario and attribution analysis to determine portfolio tolerance to adverse changes. Research Data Analyst, Center for Computational Research, SUNY Buffalo, Jan10Nov13 Modeling accurately Nuclear Magnetic Resonance (NMR) parameters on large and heavy nuclei systems with biological usefulness using Quantum Espresso/Fortran/C++/MATLAB/R in a large High Perf Cluster. Utilized Hadoop MapReduce software framework to conveniently write applications which process large volume of biological data of in a computer cluster environment. Teaching/Research Assistant, University of Connecticut Aug08Dec09. Experience in molecular modelling; virtual ligand screening; computationally driven lead optimization; ligand-based drug design; molecular dynamics; homology modelling; quantum mechanics and chemin- formatics. Teaching assistant for general chemistry and chemistry for engineers. Course work in Drug design, Characterization techniques in chemistry and material science, Spectroscopic techniques, Quantum chemistry etc. Teaching assistant for general chemistry and chemistry for engineers. Business Analyst, Barclays Bank Jun05Aug08 Wrote and executed SAS scripts based on business needs (daily,weekly and monthly reports including adhoc requests). Extensive use of Proc SQL and SAS MACROS to accomplish tasks. Utilized R to cluster customers into segments that enabled bank to have a better control of credit risk. Inititiated data mining approaches to improve customer base - by cross-selling to existing customers using a combination of mainly SQL, Excel and SAS.Candidate's Name 3 Used statistical softwares R/SAS data mining capabilities to come up with association rules between prod- ucts and services that Barclays bank offers. Processed and analyzed large data sets on Barclays bank emerging markets, monitor portfolio for trends and report to management (main products home/business/premier/loans, credit cards and OTC derivatives. Developed spreadsheets, macros, queries for effective monitoring of retail credit portfolio. Managed the collection (SQL extraction) and review of Barclays Africa portfolio default data, which involved the calculation of realized losses and realized exposure at default to support the banks estimation of default, usage given default and Loss given default (LGD). |
