onsite
Fraud Data Scientist - Billie
Data Scientist
Lead the development of advanced fraud detection models using Python and machine learning, leveraging SQL and big data tools to protect B2B payment transactions on a scalable platform.
About the role
Key Responsibilities
- Design, build, and deploy machine‑learning models to detect and prevent fraud in real‑time payment flows.
- Analyze large volumes of transactional data using SQL and Python to uncover patterns and anomalies.
- Collaborate with product, engineering, and risk teams to integrate models into the BNPL platform.
- Monitor model performance, conduct root‑cause analysis, and iterate for continuous improvement.
- Document methodologies, maintain reproducible pipelines, and share insights with stakeholders.
Requirements
- Strong experience with Python, SQL, and data‑science libraries (scikit‑learn, pandas, numpy).
- Proven track record in fraud detection or related risk analytics.
- Familiarity with big‑data ecosystems (Spark, Hadoop) and cloud services (AWS, GCP).
- Excellent problem‑solving skills and ability to communicate complex findings clearly.
- Experience with model deployment and monitoring in production environments.
Skills
pythonmachine learningsql