Research Scientist, Applied Machine Learning - Credit
MONEE SG PRIVATE LIMITED
Singapore, Singapore
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Phd in computer science or related field
Applied machine learning research experience
Credit risk modeling expertise
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MONEE SG PRIVATE LIMITED is seeking a Research Scientist in Applied Machine Learning for Credit to enhance credit risk modeling through innovative methodologies. The ideal candidate will possess a PhD in a relevant field, experience in applied machine learning, and a strong understanding of financial AI.
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Job Summary
The role involves researching and developing advanced machine learning methodologies to improve credit risk modeling across underwriting, pricing, and portfolio optimization.
Candidates must possess a PhD in a relevant discipline and have prior experience applying cutting-edge ML techniques like deep learning and reinforcement learning to financial problems.
The successful candidate will partner with Risk, Data Science, Product, and Engineering teams to translate validated research prototypes into scalable, production-ready solutions.
Matching Summary
Match Score: 75
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MONEE SG PRIVATE LIMITED is seeking a Research Scientist in Applied Machine Learning for Credit to enhance credit risk modeling through innovative methodologies. The ideal candidate will possess a PhD in a relevant field, experience in applied machine learning, and a strong understanding of financial AI.
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Skills & Requirements
Must-have
PhD in Computer Science or related field
Applied machine learning research experience
Credit risk modeling expertise
Deep learning and reinforcement learning skills
Causal inference and graph learning knowledge
Nice-to-have
Experience in fintech or internet industry
Ability to explain complex trade-offs to stakeholders
Knowledge of large-scale pre-trained models
Strong experimental rigor and ablation studies
Background in financial engineering
Key Requirements
PhD in Computer Science, Machine Learning, or Quantitative Finance
Prior experience in applied ML research or model development
Strong background in hypothesis formulation and error analysis