Data Scientist - Consumer Fraud Analytics @ From August 2015 to Present (5 months) Data Scientist - Healthcare Analytics @ • Use a bespoke challenge question methodology and hypothesis testing environment to derive material root-cause insights into what drives client project engagements. • Acquire, model, extract, aggregate, validate, cleanse, filter, enrich, benchmark, and document programmatic information retrieval algorithms to build large and dynamic data sets from public, client, and proprietary structured and unstructed disparate data sources. • Construct multi-functional discovery workbenches to present clients with visualizations of the statistically significant patterns, trends, and findings of analysis work. • Architect predictive and prescriptive analytic models to identify behavior or change workflows to achieve optimal results through such techniques as: statistics, data/text mining, supervised and un-supervised machine learning, and algorithm development. • Both lead, and assists other data science consultants, project managers, strategic sales personal, SMEs and C-level executives, as well as client contacts in 6 of 7 major consulting engagements. From October 2014 to July 2015 (10 months) Director, Actuarial and Underwriting @ • Lead a multi-office team of 10 statisticians/business analyst in managing health plans of 100+ clients with annual revenues over $80MM. • Acted as SME in client C-level executive and federal government presentations with rich and effective visualizations and client financial reports. • Predicted client expenditures with use of time series and logistic regression modeling, automated ETL process, from SQL server using ODBC connection, for client financial reporting, and constructed visualizations for client presentation/sales meetings. • Hired and mentored junior associates and developed their skills in analytics, business strategy, and client presentations. Promoted assistants to senior analysts. • Provided proof of conception for implementation of Tableau Desktop BI reporting system. • Progressed from Actuarial Assistant, to Senior Actuary Analyst to Director of Actuarial and Underwriting. From April 2008 to October 2014 (6 years 7 months) Risk Management Intern @ • Visualized frequentist statistics and time series measures. • Simulated discrete-time outlier-value economic risk models. • Created financial parametric probabilistic models for pricing, risk and sensitivity analysis. • Engineered a non-linear optimization algorithm for solving a non-parametric probability model. From April 2007 to July 2007 (4 months) Greater San Diego Area

Graduate Certificate, Management Science and Engineering @ Stanford UniversityCoursera signature track, Data Science @ The Johns Hopkins UniversityB.S., Management Science w/Minor in Mathematics @ University of California, San Diego From 2004 to 2007 Extension coursework @ University of California, BerkeleyHigh School @ San Marin High School Christian Lenaburg is skilled in: R, Data Science, Machine Learning, Data Visualization, Predictive Analytics, Tableau, Algorithms, Business Intelligence, Econometrics, Time Series Analysis, Statistics, Data Mining, Quantitative Analytics, Data Analysis, Analytics