Applied Scientist I, Buyer Risk Prevention (BRP)

Key job responsibilities
Apply machine learning and statistical techniques to build and improve risk management models

Analyze large-scale historical data to identify risk patterns and emerging trends

Develop, validate, and deploy innovative models under the guidance of senior scientists

Experiment with emerging technologies, including GenAI/LLMs, to enhance automation and risk evaluation

Collaborate closely with software engineers to implement models in real-time production systems

Partner with operations and business teams to improve risk policies and operational efficiency

Build scalable, automated pipelines for data analysis, model training, and validation

Monitor model performance and provide clear reporting on key risk and business metrics

Research and prototype new modeling approaches to improve system performance

Basic Qualifications

- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Master's degree in Engineering, Computer Science, Machine Learning, Operations Research, Statistics, or related fields
- Experience building machine learning models or developing algorithms for business application

Preferred Qualifications

- Experience implementing algorithms using both toolkits and self-developed code
- Have publications at top-tier peer-reviewed conferences or journals