2 days ago
San Jose, CA, USAStaff+
Base Salary
$197k - $334k/yr
Responsibilities
- Manage the FSI Data Integration Project with risk models and coordinate feature exposure with infrastructure and online engineering teams.
- Verify the existence and quality of online variables and collaborate with analytics and data science teams to enumerate and compare features.
- Support risk models across fraud domains including account takeover, collusion, seller risk, and credit risk.
- Develop a new risk model based on linking features using graph-based tools, embedding features, proof-of-concept experimentation, and performance comparisons.
- Build automated tools for ML experimentation, deployment, and monitoring.
- Transform FSI data into graph infrastructure and apply graph data science insights to linking automation.
- Automate detection of new risky features.
- Collaborate with cross-functional teams to align ML outputs with business objectives and production decision systems.
Requirements
- Master’s degree or foreign equivalent in Computer Science, Engineering, or a closely related field plus four years of relevant experience, or a bachelor’s degree or foreign equivalent in those fields plus six years of relevant experience.
- Four years of experience developing machine learning models for financial fraud detection.
- Four years of experience translating stakeholder requirements into ML problem formulations, KPIs, evaluation metrics, and success criteria.
- Four years of experience designing and developing end-to-end ML solutions from data collection and feature engineering through deployment and maintenance.
- Four years of experience automating ML data collection, training, model encoding, and production deployment.
- Four years of experience with Python-based libraries including scikit-learn, pandas, NumPy, and Keras.
- Four years of experience with large-scale tabular datasets in cloud-based data warehouse environments.
- Four years of experience encoding and optimizing production ML models using serialization frameworks such as ONNX.
- One year of experience with embedding representation methods for tabular data.
- Four years of experience collaborating with business strategy, engineering, data infrastructure, and data science teams.
Benefits
- Telecommuting is permitted and work may be performed from anywhere in the US.
- PayPal’s general balanced hybrid model offers three days in the office and two days at the employee’s choice of the PayPal office or home workspace for most employees.
- Benefits include generous paid time off, healthcare coverage for employees and families, financial security resources, and mental health support.
- The role is listed for 40 hours per week, Monday through Friday, 9:00 a.m. to 5:00 p.m.
- Additional compensation may include an annual performance bonus, equity, or other incentive compensation.
Tech Stack
Categories
About PayPal
PayPal builds digital payments platforms for consumers and merchants, including PayPal, Venmo, and Xoom, supporting online, in‑app, and in‑person checkout and peer‑to‑peer transfers. It earns primarily from transaction and merchant processing fees, plus value‑added services such as risk management and branded credit. Founded in 1998 and headquartered in San Jose, California, PayPal operates in roughly 200 markets and is a public company traded on NASDAQ.