Sr Data Scientist – Financial Crimes Detection, PayPal World
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Key skills for this role
About the Role
PayPal seeks a Senior Data Scientist to build AML and fraud detection models for its new PayPal World platform. You will design transaction monitoring rules and ML models, develop feature engineering pipelines, and collaborate with compliance teams to combat money laundering in a multi-wallet payment network.
Key Skills for This Role
Responsibilities
- Design and implement transaction monitoring rules and machine learning models to detect money laundering, structuring & fraud across PayPal World's multi wallet payment rails
- Develop and maintain feature engineering pipelines in BigQuery, creating reusable primitives (velocity, growth ratios, concentration, dormancy signals)
- Partner with data engineering teams to define data requirements for new transaction types flowing through the network platform
- Analyze transaction patterns across jurisdictions to identify emerging typologies unique to interoperable payment networks
- Build model validation frameworks including back testing against historical cross platform activity and false positive analysis
- Translate detection outputs into actionable intelligence for compliance investigators, designing alert packages
- Collaborate with compliance policy teams across multiple jurisdictions to ensure detections satisfy local regulatory obligations
- Produce clear documentation of detection methodology, threshold rationale, and model performance for regulatory examination
- Advise product and engineering teams on financial crime risk implications of new PayPal World features before they launch
Requirements
- 5+ years of experience building AML/fraud detection models or transaction monitoring systems at a financial institution, fintech, or payment network
- Strong SQL skills with experience writing complex analytical queries against large scale transactional datasets (BigQuery, Snowflake, or similar)
- Python proficiency for data analysis, feature engineering, and model development (pandas, scikit learn, or equivalent)
- Experience with BigQuery ML, TensorFlow, XGBoost, or similar frameworks for classification and anomaly detection
- Understanding of AML regulatory frameworks (BSA/FinCEN, AUSTRAC, EU AMLD, FATF guidelines)
- Experience working with payment network data — understanding of P2P flows, funding instruments, settlement processes
- Comfort operating in ambiguity: ability to define your own workstreams, make progress with incomplete data
- Experience partnering with compliance investigators to understand how detections translate to actionable cases
- Familiarity with graph based analysis or network detection methods
- Strong communication skills — ability to explain model behavior to non technical compliance stakeholders
Full Job Posting
Job Summary
- As a Data Scientist, you will apply your strategic and analytical skills to build monitoring solutions to combat money laundering.
- This job will lead development and implementation of advanced data science models and algorithms.
- You will work with stakeholders to understand requirements, analyze and derive insights from large volumes of data.
Essential Responsibilities
- Lead the development and implementation of advanced data science models.
- Collaborate with stakeholders to understand requirements.
- Drive best practices in data science.
- Ensure data quality and integrity in all processes.
- Mentor and guide junior data scientists.
- Stay updated with the latest trends in data science.
Additional Responsibilities
- Design and implement transaction monitoring rules and machine learning models to detect money laundering, structuring & fraud, across PayPal World's multi wallet payment rails.
- Develop and maintain feature engineering pipelines in BigQuery, creating reusable primitives (velocity, growth ratios, concentration, dormancy signals) that serve multiple detection use cases.
- Partner with data engineering teams to define data requirements for new transaction types flowing through the network platform, ensuring detection relevant fields are captured from the start.
- Analyze transaction patterns across jurisdictions to identify emerging typologies unique to interoperable payment networks.
- Build model validation frameworks including back testing against historical cross platform activity and false positive analysis to ensure detections are operationally sustainable.
- Translate detection outputs into actionable intelligence for compliance investigators, designing alert packages that provide sufficient context for efficient case resolution.
- Collaborate with compliance policy teams across multiple jurisdictions (FinCEN, AUSTRAC, CSSF, and others) to ensure detections satisfy local regulatory obligations as the platform expands.
- Produce clear documentation of detection methodology, threshold rationale, and model performance for regulatory examination and internal model governance review.
- Advise product and engineering teams on financial crime risk implications of new PayPal World features, payment flows, and partner integrations before they launch.
Minimum Qualifications
- Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
Preferred Qualifications
- 5+ years of experience building AML/fraud detection models or transaction monitoring systems at a financial institution, fintech, or payment network.
- Strong SQL skills with experience writing complex analytical queries against large scale transactional datasets (BigQuery, Snowflake, or similar cloud data warehouses).
- Python proficiency for data analysis, feature engineering, and model development (pandas, scikit learn, or equivalent).
- Experience with BigQuery ML, TensorFlow, XGBoost, or similar frameworks for classification and anomaly detection.
- Understanding of AML regulatory frameworks (BSA/FinCEN, AUSTRAC, EU AMLD, FATF guidelines) and how detection systems map to regulatory obligations.
- Experience working with payment network data — understanding of P2P flows, funding instruments, settlement processes, and the distinction between sender side and receiver side risk signals.
- Comfort operating in ambiguity: ability to define your own workstreams, make progress with incomplete data, and adapt as platform architecture evolves.
- Experience partnering with compliance investigators to understand how detections translate to actionable cases.
- Familiarity with graph based analysis or network detection methods for identifying linked accounts, collusion, or money movement networks.
- Strong communication skills — ability to explain model behavior to non technical compliance stakeholders and defend methodology in regulatory contexts.
Nice to Have
- Experience building detection systems for a multi party payment network (Zelle, RTP, SWIFT, card networks) where counterparty visibility is limited.
- Exposure to cross border compliance challenges: multi jurisdictional filing requirements, sanctions screening across networks, or CDD/EDD processes for foreign PEPs.
- Experience with Airflow or similar orchestration tools for scheduling batch detection pipelines.
- Background in feature store design or reusable detection primitive architectures.
- Prior experience in a 'zero to one' build — standing up a detection function for a new product or platform from scratch.
Pay Range
- Scottsdale, Arizona: $123,500.00 $183,700.00 Annually
- Omaha, Nebraska: $123,500.00 $183,700.00 Annually
- Additional compensation may include an annual performance bonus, equity, or other incentive compensation.
Work Model
- PayPal's balanced hybrid work model offers 3 days in the office for effective in person collaboration and 2 days at your choice of either the PayPal office or your home workspace.
Our Benefits
- Comprehensive, choice based programs to support all aspects of personal wellbeing—physical, emotional, and financial.
- Generous paid time off, healthcare coverage for you and your family, and resources to create financial security and support your mental health.
Who We Are
- PayPal has been revolutionizing commerce globally for more than 25 years.
- We operate a global, two sided network at scale that connects hundreds of millions of merchants and consumers.
- Our core values are Inclusion, Innovation, Collaboration, and Wellness.
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