Sr Data Scientist

PayPal
San Jose
Workplace: OnsiteFull timeUSD 174,783 - 243,500 annuallyFunction: Data Science & Machine LearningExperience: 3+ yearsEducation: mastersSkills: ["Cross-functional collaboration","Presenting insights","Mentoring","Analytical thinking","Experiment design"]

Apply advanced analytics and statistical modeling to large-scale payment and transactional data to detect and prevent fraud in real time. Build risk assessment solutions that balance loss appetite, user experience, and business KPIs, and evaluate model impact via rigorous A/B testing. Create Tableau/Power BI dashboards and cloud SQL data pipelines, perform root-cause analysis, and partner with product, engineering, and leadership while mentoring junior analysts.

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FursaFursa
PayPal
PayPal
1 day ago

Sr Data Scientist

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Source: Company careers pageValidated by: Fursa AI
Last checked: 7 hours agoStatus: Live

Job Summary

Apply advanced analytics and statistical modeling to large-scale payment and transactional data to detect and prevent fraud in real time. Build risk assessment solutions that balance loss appetite, user experience, and business KPIs, and evaluate model impact via rigorous A/B testing. Create Tableau/Power BI dashboards and cloud SQL data pipelines, perform root-cause analysis, and partner with product, engineering, and leadership while mentoring junior analysts.
Location: San Jose
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Research and analyze multi-dimensional data sets, implement continuous monitoring, and develop algorithmic logic to identify and prevent fraudulent activity in real time.
  • •Design, construct, and validate statistical models that transform raw transactional data into actionable fraud detection insights.
  • •Develop and maintain real-time risk assessment solutions that balance loss appetite, user experience metrics, and product financial performance KPIs.
  • •Run rigorous A/B testing for fraud detection models and risk controls, and enhance models based on statistical significance and findings.
  • •Create and maintain Tableau/Power BI dashboards, perform root-cause analysis of fraud and security breaches, and partner with product and risk engineering teams to deliver mitigation requirements.

Pay and Benefits

Salary: USD 174,783 - 243,500 annually
Equity and Bonus:Equity
Perks:Health InsurancePaid LeaveLearning Budget

Key Requirements

  • •Master’s degree (or foreign equivalent) in Data Science, Mathematics, or a closely related field, plus 3 years of experience in the role or related occupation.
  • •Experience performing root cause analysis on fraud cases in financial transaction systems and implementing data-driven mitigation strategies in production.
  • •3+ years using Python (NumPy, Pandas) for fraud modeling, feature engineering, and applying Scikit-learn to develop fraud models on large-scale transaction datasets.
  • •Experience building Tableau dashboards to monitor fraud risk KPIs for decision-making.
  • •Experience writing complex SQL queries on cloud-based data platforms and working with distributed data systems to build and maintain data pipelines and workflows in data warehouse environments.
Experience:3+ yearsFraud detectionPaymentsFinancial transactionsRisk managementReal-time analytics
Education:Master's in Data Science, Mathematics, or a closely related field
Skills:Cross-functional collaborationPresenting insightsMentoringAnalytical thinkingExperiment design
Tech Stack:PythonNumPyPandasScikit-learnTableauPower BISQLGitHubH2O

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