Data Analysis/Predictive Modeling/SAS statistician- SF 94111

[Polinnka]

Apply predictive modeling skills & Insurance knowledge to design and develop solutions for P&C Insurance.
* Leverage skills in handling very large datasets, perform sampling, & determine adjustments to test and compensate for data bias.
* Apply multiple methodologies for variable reduction and selection, clustering, segmentation & transformation.
* Identify predictive modeling technique(s) most appropriate for the problem (Generalized Linear Models, Logistic Regression, Decision and Regression Trees, Neural Networks, etc.) & develop multiple candidate models.
* Perform model validation to determine model lift & accuracy & test for reliability & stability of models. Use multiple statistics & measures to select final model.

Qualifications:

Masters degree (Ph.D. preferred) in quantitative or actuarial field is required
* 3+ years professional experience building predictive models on very large datasets required
* 18 months professional experience applying predictive modeling techniques in P&C insurance required
* Demonstrated knowledge of data reduction techniques, clustering, and Generalized Linear Models (GLM) required
* 2+ years professional SAS experience using Logistic and GLM modeling is required
* Demonstrated knowledge of the business of insurance and insurance data required

e-mail: v lichku

[Пушыстег]

Опыт в insurance обязателен на 100%?

[Polinnka]

predictive modeling + large datasets обязательно..
morgage - credit - fraud подходит; bio - нет.
ето больше stat/math позиция; не - data analysis/programming..