PayPal is looking to quantify the predictive value of internal and external features and define how a data marketplace measures, validates, and ranks signals across risk domains to shape the foundations of a customer-facing risk signal catalog.
Requirements
- Deep expertise with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
- Extensive experience with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
- Proven track record of leading the design, implementation, and deployment of machine learning models.
- Strong hands-on experience with Python, SQL, and model evaluation frameworks.
- Expertise in predicting and monitoring feature importance
- Familiarity with building blocks of distributed systems and technologies like GCP and Kubernetes.
- Experience working with financial or behavioral datasets.
Responsibilities
- Define and drive the strategic vision for machine learning initiatives within the team.
- Lead the development and optimization of machine learning models.
- Oversee the preprocessing and analysis of large datasets.
- Deploy and maintain ML solutions in production environments.
- Collaborate with cross-functional teams to integrate ML models into products and services.
- Monitor and evaluate the performance of deployed models, making necessary adjustments.
- Mentor and guide junior engineers and data scientists.
Other
- 8+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
- Excellent communication skills to translate complex analytical insights into product recommendations.
- Ability to work in a hybrid work model with 3 days in the office and 2 days at home.
- Commitment to diversity and inclusion
- Ability to work with a diverse workforce reflective of the merchants, consumers, and communities that PayPal serves
