À propos
Responsibilities
Apply advanced statistical techniques and algorithms on complex datasets to build statistical or financial models for predicting risk and revenue and driving actionable business insights for Bill Me Later’s product or customer‑level credit risk management.
Mine data—including user profile and transaction details—to solve risk problems that involve classification, clustering, pattern analysis, sampling, and simulations.
Design and refine a valuation framework that enables PayPal to extend credit with a comprehensive view of each decision’s NPV.
Collaborate with product, data science, and finance teams to enhance underwriting and optimize credit portfolio performance.
Identify emerging risks or opportunities and propose mitigation strategies.
Identify optimal data sources and process improvements to enhance risk management, customer experience, and growth.
Establish detailed KPI tracking to monitor the credit‑card program’s health and simplify insights for stakeholders and senior management.
Present regular updates to senior management on business health, highlighting successes, challenges, and actionable insights, along with plans for addressing key issues.
Partial telecommuting permitted from within a commutable distance.
Qualifications Minimum Requirements:
Master’s degree in Computer Science, Economics, Mathematics, Statistics, Engineering, or another quantitative‑related field plus two years of experience in credit‑risk analytics or strategy in consumer lending.
Special Skill Requirements:
Experience in forecasting techniques/algorithms and automation with Python.
Machine learning (model development/deployment; optimization including parameter tuning, dimensionality reduction, feature selection, and model validation).
Predictive analytics and segmentation (classification models, regression models, and statistical analysis).
Experimental design (A/B testing).
Profit & Loss (P&L) analytics.
Credit risk management / credit risk analytics.
Credit bureau analytics.
Python (pandas, numpy, and sklearn packages).
SQL tools: Google BigQuery and Teradata.
Data visualization (Tableau, Amplitude, and Q‑monitor).
Database management: Big data and cloud (Hadoop, Hive, Stampy, Teradata, and Google BigQuery).
Pay & Benefits The base pay for this role will depend on your experience and expertise. The expected pay range in Chicago, IL is $106,000 to $180,000 per annum, for 40 hours per week (Monday‑Friday, 9:00 a.m. to 5:00 p.m.). Additional compensation may include an annual performance bonus, equity, or other incentive compensation as applicable.
EEO Statement PayPal provides equal employment opportunity (EEO) to all persons regardless of age, color, national origin, citizenship status, physical or mental disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity and/or expression, genetic information, marital status, status with regard to public assistance, veteran status, or any other characteristic protected by federal, state, or local law. In addition, PayPal will provide reasonable accommodations for qualified individuals with disabilities. If you are unable to submit an application because of incompatible assistive technology or a disability, please contact us at
paypalglobaltalentacquisition@paypal.com .
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Compétences linguistiques
- English
Avis aux utilisateurs
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