Predictive Statistical Modeler – (SAS, GLM, Survival Analysis, Customer Lifetime Value)
The group will provide state of art statistical insights on modeling techniques, data manipulation, model building and model implementation. Candidates must be able to manage statisticians who build predictive models, understand the core assumptions, and explain the outcomes of these models to senior management. The candidates must have advanced statistical modeling skills (MCMC, Bayesian, Machine Learning, GLM, OLS, ARIMA), current coding in (R, Stata, SPSS, Python, C++), current experience with both Windows and UNIX/Linux operating systems, and expert knowledge of SAS. This is a great opportunity for an advanced statistician who is looking to apply state of the art analytics and statistical programming to transform the way a major insurance organization looks at, manages and forecasts risk. The firm will look at candidates with 3-15 years of experience applying advanced statistical modeling to solving complex business problems; leadership experience, and superior oral and written communication skills.
Candidates from Consumer Credit Statistical roles are encouraged to apply. Insurance industry knowledge is a plus but not a requirement. Working remotely is possible for more experienced candidates.
Keywords: Statistician, SAS, Insurance Analytics, Data Manipulation, Model Validation, UNIX, Linux, Machine Learning, Customer Lifetime Value, Survival Analysis,
Refer to Job#20037-EFC and email MS Word attached resume to Jim Geiger, jeg@analyticrecruiting.com or register online at www.analyticrecruiting.com choosing Jim Geiger as your contact recruiter.
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