Nicholas Guerrero

http://www.linkedin.com/in/nicholasguerrero

https://github.com/NicholasGuerrero/Machine_Learning_Builds 1912 Curtis Ave California 90278 310-***-**** acyj8f@r.postjobfree.com Education

B.A. in Quantitative Economics, May 2016, Whittier College Emphasis in Analytical and Business Economics

Honors : Recipient of John Greenleaf scholarship (2012), Deans List (2012-2015), Elected into International Economics Honor Society Omicron Delta Epsilon

Re l evant Courses : Achieved Success in Econometrics, Finance, Economics, Derivatives, Financial Modeling, Accounting, Calculus, Differential Equations, and Computer Science classes Proj ec ts : Macroeconomic Factors: An Explanatory Source of Mergers and Acquisitions Paper: This paper considers what factors, measured by macroeconomic explanatory variables, explain the percent change in mergers and acquisition frequency. The data set consists of an annual panel of 68 different countries from the years 1966-2015.

Current data analyst at City National Bank with newly acquired skills from working on Dodd-Frank Act CCAR stress testing, an insatiable curiosity and ability to traverse large sets of structured, semi-structured, and unstructured data. Well-versed in analytical projects that require work with large data sets and the use of intermediate level computer programming in R and Python. Able to leverage a heavy dose of mathematics and applied statistics with visualization and a healthy sense of exploration. Sample code of machine learning algorithms built from scratch can be found on personal Github repository. Topics and data sets included. Competencies

Computer programming competencies Analytical competencies v R v Advanced Microsoft Excel

v VBA v Data Analysis and Visualization

v Stata v Accounting Knowledge

v Python (pandas, sklearn, matplotlib, others..) v Team Building v SQL & NoSQL (Mongo) v Leadership

Experience

SIEML (Summer Institute for Emerging Managers and Leaders) Participant, UCLA/UC Davis CA, 2013-2014 v Collaborated in the development of a consulting package presenting case study to UCLA Anderson faculty v Moderated communication between team members increasing performance standards and work flow process v Studied under company executives, observed their expertise and listened to their advice, gained a greater understanding of the business environment.

CCAR Data Analyst, City National Bank, Los Angeles 555 South Flower, Sept. 2016 – Present v Employed Excel, VBA programming, and SQL programming to train and call back input loan data provided by Cushman & Wakefield to be uploaded into Credit Risk SQL Database for CCAR modeling. v Tracked 2,719 loans at loan and property levels as they went through CCAR modeling process giving the CCAR implementation team a clear understanding of the completion percentage of the project. v Generated analytic reports that were used as a template for the remediation of loan data between CNB and C&W members to address missing values and values that differed for in house auditing purposes. v Documented and processed all work in an H2 documentation report format specified by the Federal Reserve to be given to outside auditing firm during final steps of the project. Data modeler, Self-Employed, Whittier CA, September 2015 – May 2016 v Modeled the environment within the game to accurately assess the probability of winning a match which gave players feedback based off mathematical metrics

v Executed the aggregation of data from the game’s server into a SQL database so that calculations could be performed. v Investigated other modeling techniques to optimize the algorithm, giving users the most accurate results v Invented unique method to determine how to analyze player performance using an elo system.