PayPal Fraud Science Data Engineer 

United States, Arizona, Scottsdale 

808126091

Your day to day will include:

• Engineernew linking featuresfrom raw data for use in FSI’s fraud linking framework.

• Hunt for new data andintelligence thatcan be used to link fraudulentaccounts across acomplex data platform.

• Maintain metricstracking featureperformance.

• Apply statisticalmethods for combining multiple data points to identify fraud patterns.

• Continuouslyimprove the speed,reliability, andscalabilityof FSI tools.

• Leverage partner

• Identify opportunities to extend FSI linking solutions with internal partners’ technology stacks for holistic fraud prevention.

What do you need to bring:

• Skilled in performing exploratory data analysis to identify patterns, trends, and anomalies.

• Proficient incleaning and preprocessing large datasets to ensure accuracy and consistency.

• StrongSQL experience tocreate, maintain, and optimize complex queries and database structures.

• Advanced proficiencyin Python. Experiencewith libraries and tools for string processing and pattern recognition.

• Understanding of financially motivated cybercrime trends and typologies.

• Team player, energetic personality, curious, able to work efficiently in a fast paced, changing environment.

· Experience designing data models and building scalable data pipelines using tools like Airflow, dbt, or Spark.

· Proficient in writing clean, production-grade code and translating prototypes into reusable software components.

· Comfortable with APIs, system integrations, and deploying features into production in collaboration with engineers and analysts.

· Familiar with cloud-based data architectures in GCP, distributed systems, and container orchestration tools like Docker or Kubernetes.

· Skilled in version control using Git, with experience in CI/CD workflows and ensuring data service reliability through monitoring and observability tools.

Our Benefits:

Any general requests for consideration of your skills, please