Statistical Modeler, PayPal Inc. San Jose, CA

This role will be responsible for designing and developing predictive models to support PayPal marketing’s customer acquisition and retention efforts.

Key Responsibilities:

§ Develop propensity models and segmentation to enable more accurate targeting for various marketing programs.

§ Profile buyers and sellers using both internal and third-party data, and develop customer clusters to support the formulation of product and marketing strategies.

§ Design customer churn analysis to identify at-risk segments for reactivation campaigns.

§ Work with internal clients to develop and deliver actionable recommendations.

§ Work with internal technology team to score database to enable model deployment

Required Qualifications:

§ Master Degree or above in Statistics, Economics, Operation Research or other quantitative field. 

§ 5+ years hands-on experience performing statistical modeling and analysis on large volumes of data.  Solid background in multivariate analysis, including linear & logistic regression, factor analysis, cluster analysis, decision trees, etc.

§ Proficient in using SAS, SPSS or other statistical tools. Experience in Affinium Model a plus

§ Advanced Excel skills (eg: Pivot Tables, Advanced Formulas & Charting etc) is required.

§ Excellent oral and written communication skills.  Demonstrated ability to translate sophisticated analytics models into stories that can be easily understood by business owners and senior executives.

§ Ability to work effectively and execute within deadlines in a fast-paced environment.

Please send resumes to Holly Zhang holzhang@paypal.com

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