Responsibilities
- Develop machine learning (ML) models for fraud detection and risk prediction.
- Conduct feature engineering, data analysis, and A/B testing to improve model performance.
- Deploy real-time decision algorithms supporting global business operations.
- Build and maintain real-time risk decision engines and monitoring pipelines to detect and respond to emerging threats.
- Collaborate with cross-functional teams to integrate ML-driven solutions into production.
- Explore new algorithms and technologies to strengthen global risk control capabilities.
Basic qualifications
- Bachelor’s degree in Engineering, Computer Science, Mathematics, or a related technical field.
- 3+ years of professional experience as a machine learning engineer or applied research scientist in risk control or fraud detection.
- A deep understanding of modern algorithms and approaches to ML, NLP, and LLMs.
- Strong programming skills in Python, with experience using TensorFlow or PyTorch.
- Demonstrated ability to work independently with minimal guidance; proactively manage tasks and priorities across multiple projects; analyze and execute work efficiently; collaborate effectively with cross-functional teams; and thrive in fast-paced, results-driven environments.
- Effective communication skills in Chinese and English.
Preferred qualifications
- Experience in e-commerce or fintech risk management (e.g., cross-border fraud, credit scoring).
- Experience with UK and European business environments.
Benefits
- A dynamic and challenging work environment in a leading global e-commerce company.
- The opportunity to work with a diverse international team and make a significant impact on JD.com’s global presence.
- A competitive salary and benefits package, including health insurance, retirement plans, and performance bonuses.
Tags & focus areas
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