Machine Learning Engineer Job at PayPal in Chicago

Job Summary

Senior Machine Learning Engineer focused on building advanced fraud prediction models for identity, onboarding, authentication, abuse, scam, and product‐specific fraud prevention.

Responsibilities

• Design and implement core decision models for identity, onboarding, authentication, abuse, scam, and product‐specific fraud prevention.


• Develop and refine algorithms for detecting anomalies and identifying potential fraud patterns.


• Apply supervised learning techniques to build predictive models that accurately identify fraudulent activities.


• Utilize continual learning methods to continuously improve model performance and adapt to new fraud tactics.


• Collaborate with cross‑functional teams (tech, operations, product) to integrate fraud prediction models into systems and processes.


• Conduct experiments, analyze results, and interpret findings to drive innovation and enhance decision‑making.


• Ensure data integrity and consistency by working closely with stakeholders to address critical data challenges.


• Promote and maintain a data‐driven culture by engaging with internal teams and advocating best practices in data science and fraud prevention.

Requirements

• Master’s degree or PhD in Computer Science, Statistics, Data Science, Machine Learning, Artificial Intelligence, or a related quantitative field (STEM).


• 5+ years of experience in Data Science, ML Engineering, or AI Research roles with expertise in building and deploying real‑world predictive models.


• Strong understanding of anomaly detection, supervised learning techniques, and experiential learning methods; experience in fraud prevention is a plus.


• Excellent interpersonal, written, and verbal communication skills, with experience collaborating across multiple business functions.

Preferred Qualifications

• Familiarity with decision models for identity and authentication.


• Experience in fraud prevention and detection.


• Experience driving data instrumentation for experimentation and large‑scale data collection.


• Familiarity with real‑time systems that incorporate feedback and continuous learning.


• Knowledge of reinforcement learning, contextual bandits, sequence models, optimization, or graph mining.

Compensation

• Base salary ranges by location:
  
  
  
  • Chicago, IL: $117,500 – $174,350 annually
  
  
  • San Jose, CA: $129,500 – $191,950 annually
  
  
  • Austin, TX: $117,500 – $174,350 annually
  
  
  • Scottsdale, AZ: $111,500 – $165,550 annually
  
  
  • Omaha, NE: $111,500 – $165,550 annually
  
  
  
  


• Potential for annual performance bonus, equity, or other incentive compensation.

Equal Employment Opportunity

PayPal provides equal employment opportunity to all persons regardless of age, color, national origin, citizenship status, disability, race, religion, creed, gender, sex, pregnancy, sexual orientation, gender identity, genetic information, marital status, public assistance status, veteran status, or any other characteristic protected by law. PayPal will provide reasonable accommodations for qualified individuals with disabilities.