Role: Machine Learning Engineer AI Fintech
Location: Singapore
We are partnering with a leading AI Fintech seeking a Machine Learning Engineer with expertise in AI/ML banking models and fraud analytics. You will design predictive models detect fraud patterns and collaborate with Risk Product and Engineering teams to deliver data-driven solutions.
Responsibilities:
- Build and deploy machine learning models for credit risk payments and fraud detection.
- Analyze transactional data to identify fraud patterns and emerging risks.
- Perform feature engineering model training validation and monitoring.
- Collaborate with cross-functional teams to implement models into production systems.
- Ensure all models meet regulatory and compliance standards.
Requirements
- Bachelors or Masters degree in Computer Science or IT
- 3 years of experience in machine learning ideally with a focus on banking or fraud analytics.
- Strong skills in Python SQL and machine learning tools; experience with GenAI and LLMs is a plus.
- Solid understanding of banking products fraud schemes and risk modeling techniques.
- Hands-on experience with supervised and unsupervised machine learning applied statistics and AI methods.
#LI-RK1
Role: Machine Learning Engineer AI FintechLocation: SingaporeWe are partnering with a leading AI Fintech seeking a Machine Learning Engineer with expertise in AI/ML banking models and fraud analytics. You will design predictive models detect fraud patterns and collaborate with Risk Product and Engi...
Role: Machine Learning Engineer AI Fintech
Location: Singapore
We are partnering with a leading AI Fintech seeking a Machine Learning Engineer with expertise in AI/ML banking models and fraud analytics. You will design predictive models detect fraud patterns and collaborate with Risk Product and Engineering teams to deliver data-driven solutions.
Responsibilities:
- Build and deploy machine learning models for credit risk payments and fraud detection.
- Analyze transactional data to identify fraud patterns and emerging risks.
- Perform feature engineering model training validation and monitoring.
- Collaborate with cross-functional teams to implement models into production systems.
- Ensure all models meet regulatory and compliance standards.
Requirements
- Bachelors or Masters degree in Computer Science or IT
- 3 years of experience in machine learning ideally with a focus on banking or fraud analytics.
- Strong skills in Python SQL and machine learning tools; experience with GenAI and LLMs is a plus.
- Solid understanding of banking products fraud schemes and risk modeling techniques.
- Hands-on experience with supervised and unsupervised machine learning applied statistics and AI methods.
#LI-RK1
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