Related skills
sql python machine learning fraud detection data governance📋 Description
- Set the strategy: Build and scale fraud decisioning roadmap.
- Lead the team: Mentor data scientists and foster mastery.
- Architect solutions: Design real-time decision logic and data architectures.
- Model mastery: Develop fraud scoring and features from high-volume data.
- Optimise outcomes: Run experiments to improve precision and recall.
- Continuous monitoring: Track model performance and drift.
🎯 Requirements
- 6+ years in Data Science, Decision Science, or Fraud Risk.
- Degree in Statistics, Mathematics, Engineering, or similar.
- Deep knowledge of fraud typologies, financial crime, and regulatory landscape.
- SQL proficiency and at least one language; Python preferred.
- Demonstrated success building and deploying ML models at scale.
- Experience leading or mentoring technical teams in fast-paced env.
🎁 Benefits
- Culture: People-first environment with open voices.
- Learning: Regular technical talks and training opportunities.
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