Machine Learning Engineer

The Company

PayPal has been revolutionizing commerce globally for more than 25 years. Creating innovative experiences that make moving money, selling, and shopping simple, personalized, and secure, PayPal empowers consumers and businesses in approximately 200 markets to join and thrive in the global economy. 

We operate a global, two-sided network at scale that connects hundreds of millions of merchants and consumers. We help merchants and consumers connect, transact, and complete payments, whether they are online or in person. PayPal is more than a connection to third-party payment networks. We provide proprietary payment solutions accepted by merchants that enable the completion of payments on our platform on behalf of our customers.

We offer our customers the flexibility to use their accounts to purchase and receive payments for goods and services, as well as the ability to transfer and withdraw funds. We enable consumers to exchange funds more safely with merchants using a variety of funding sources, which may include a bank account, a PayPal or Venmo account balance, PayPal and Venmo branded credit products, a credit card, a debit card, certain cryptocurrencies, or other stored value products such as gift cards, and eligible credit card rewards.  Our PayPal, Venmo, and Xoom products also make it safer and simpler for friends and family to transfer funds to each other. We offer merchants an end-to-end payments solution that provides authorization and settlement capabilities, as well as instant access to funds and payouts. We also help merchants connect with their customers, process exchanges and returns, and manage risk. We enable consumers to engage in cross-border shopping and merchants to extend their global reach while reducing the complexity and friction involved in enabling cross-border trade. 

Our beliefs are the foundation for how we conduct business every day.  We live each day guided by our core values of Inclusion, Innovation, Collaboration, and Wellness. Together, our values ensure that we work together as one global team with our customers at the center of everything we do – and they push us to ensure we take care of ourselves, each other, and our communities.

Job Summary:

We are seeking a talented Machine Learning Engineer to join our team and focus on building advanced fraud prediction models. This role involves developing core decision models for various aspects of fraud prevention, including identity, onboarding, authentication, abuse, scam and product-specific models. The ideal candidate will leverage anomality detection, supervised learning, and experiential learning techniques to create robust and effective fraud prevention solutions.

Job Description:

Responsibilities

• Model Development: Design and implement core decision models for identity, onboarding, authentication, abuse, scam, product-specific models.
• Anomaly Detection: Develop and refine algorithms for detecting anomalies and identifying potential fraud patterns.
• Supervised Learning: Apply supervised learning techniques to build predictive models that accurately identify fraudulent activities.
• Continual Learning: Utilize continual learning methods to continuously improve model performance and adapt to new fraud tactics.
• Collaboration: Work closely with cross-functional teams, including tech, operations, and product teams, to integrate fraud prediction models into various systems and processes.
• Experimentation and Analysis: Conduct experiments, analyze results, and interpret findings to drive innovation and enhance decision-making processes.
• Data Integrity: Ensure data integrity and consistency by working closely with business stakeholders and engineers to address critical data challenges.
• Advocacy: Promote and maintain a data-driven culture by engaging with diverse internal teams and advocating for best practices in data science and fraud prevention.

Requirements

• Education: Master's degree or PhD in Computer Science, Statistics, Data Science, Machine Learning, Artificial Intelligence, or a related quantitative field (STEM).
• Experience: Relevant experience within Data Science, ML Engineering, or AI Research roles, with demonstrated expertise in building and deploying real-world predictive models.
• Skills: Strong understanding of anomaly detection, supervised learning techniques, and experiential learning methods. Experience in fraud prevention is a plus.
• Communication: Strong interpersonal, written, and verbal communication skills, with experience collaborating across multiple business functions.

Preferred Qualifications

• Expertise: Familiarity with decision models for identity and authentication.
• Domain Knowledge: Experience in fraud prevention and detection.
• Instrumentation: Experience driving data instrumentation for experimentation and large-scale data collection.
• Real-time Systems: Familiarity with building systems that incorporate real-time feedback and continuous learning.
• Advanced Techniques: Knowledge of reinforcement learning, contextual bandits, sequence models, optimization, or graph mining.

Subsidiary:

PayPal

Travel Percent:

0

-

PayPal is committed to fair and equitable compensation practices.

Actual Compensation is based on various factors including but not limited to work location, and relevant skills and experience.

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit https://www.paypalbenefits.com.