Sr Data Scientist

PayPal
Chicago
Workplace: OnsiteFull timeUSD 142,210 - 221,500 annuallyFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: mastersSkills: ["Stakeholder communication","Documentation","Model risk management","Experimentation design","Collaboration"]

Analyze large, complex datasets to deliver actionable insights and build robust machine learning/AI models for Net Credit Loss (NCL) forecasting, reserve setting, and ongoing model monitoring. Design and run experiments to quantify impact, enhance NCL forecasting automation, and ensure model compliance with CECL/IFRS9 and internal standards. Partner with Finance, Strategy, Collections, Risk, and Business teams to drive accurate forecasting, stress testing, and risk mitigation decisions.

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FursaFursa
PayPal
PayPal
2 days ago

Sr Data Scientist

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Source: Company careers pageValidated by: Fursa AI
Last checked: 2 hours agoStatus: Live

Job Summary

Analyze large, complex datasets to deliver actionable insights and build robust machine learning/AI models for Net Credit Loss (NCL) forecasting, reserve setting, and ongoing model monitoring. Design and run experiments to quantify impact, enhance NCL forecasting automation, and ensure model compliance with CECL/IFRS9 and internal standards. Partner with Finance, Strategy, Collections, Risk, and Business teams to drive accurate forecasting, stress testing, and risk mitigation decisions.
Location: Chicago
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Analyze large, complex datasets to extract actionable insights that inform the project roadmap.
  • •Design, develop, and implement machine learning/AI models for NCL forecasting, reserve setting, and ongoing model monitoring.
  • •Ensure models comply with internal standards and regulatory requirements (including CECL/IFRS9 where applicable).
  • •Design and analyze experiments (A/B, holdouts, quasi-experimentation) with statistical rigor to validate hypotheses and quantify outcomes.
  • •Partner with cross-functional teams to improve forecasting accuracy, support stress testing and reserve setting, monitor model performance, and assist compliance reviews and audits.

Pay and Benefits

Salary: USD 142,210 - 221,500 annually
Equity and Bonus:Equity
Perks:Health InsurancePaid LeaveLearning Budget

Key Requirements

  • •Master’s degree (or foreign equivalent) in Computer Science, Data Science, Statistics, Engineering, or a closely related field, plus five years of related experience (or Bachelor’s plus seven years).
  • •Experience developing credit risk models and collection strategies using statistical techniques.
  • •Experience in Python for data analysis and machine learning, and SQL querying including complex joins, CTEs, and window functions.
  • •Experience with machine learning algorithms such as multivariate linear regression, logistic regression, gradient boosting, decision trees, and XGBoost, including feature engineering and hyperparameter tuning.
  • •Experience with end-to-end delivery of machine learning models and collection strategies, including requirements, development, deployment, validation, and monitoring.
Experience:5+ yearsCredit riskConsumer creditFinancial servicesMachine learning
Education:Master's in Computer Science, Data Science, Statistics, Engineering, or a closely related field
Skills:Stakeholder communicationDocumentationModel risk managementExperimentation designCollaboration
Tech Stack:PythonSQLMachine LearningAICECLIFRS9A/B testingHoldoutsQuasi-experimentationGitTableauMicrosoft ExcelJiraSnowflakeApache AirflowGitHubXGBoostMultivariate linear regressionLogistic regressionGradient boosting

Eligibility

Work Authorization:Authorization required. Sponsorship not provided.

Company Brief

PayPal
Global online payments platform enabling digital and mobile payments, money transfers, and merchant services for consumers and businesses, supporting e‑commerce transactions across multiple currencies and payment methods.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: San Jose, United States
Founded: 1998
WebsiteLinkedIn