Senior Data Scientist (Large Language Model/Credit Risk Modeling) - AVP/VP
Citigroup
- Singapore
- Permanent
- Full-time
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- Drive AI/Machine Learning development and implementation especially around Generative AI Large Language Model for Wholesale Lending and Counterparty Credit Risk analytics.
- Work independently or collaboratively (depending on the circumstance) to help business stakeholders to identify analytical/technical opportunities to improve the existing process or address existing pain points.
- Work with large and complex data sets (both internal and external data) to evaluate, recommend, and support the implementation of credit risk strategies using a variety of programing and AI tools (e.g. SQL, Python, C, Spark, Sikilearn, Tensorflow, PyTorch, HuggingFace, Large Language Model etc.).
- Design and implement Early Warning Indicators for Credit Risk, Counterparty Risk, Portfolio Health, Covenant Monitoring using either traditional statistical approach or advanced AI/ML modeling, graph analytics approach.
- Design and implement statistical and risk-driven solution for Limits Management and Exception Management.
- Be actively involved in and responsible for elements of the design / implementation / coding of feature driven analytic models, including data structure / design to support the delivery of such.
- Responsible for all the Risk and Controls requirement in analytics or technical process such as documentation, testing, and ongoing performance monitoring.
- Minimum 6-10 years of working experience in AI/ML domain preferably in Finance/Risk analytics field
- Must have demonstrated ability in programing skills using Python/C/SQL/Spark for data processing and data analytics.
- Must have solid knowledge and implementation experience of basic AI/Machine Learning such as Logistics Regression, Support Vector Machine, Random Forrest, Isolation Forrest, XGBoost.
- Must have solid knowledge and implementation experience of Large Language Model pipeline: Pre-trained LLM (such as Llama, Mistral), GPT, RAG, Fine-tuning, Prompt Engineering. Vector DB, LangChain, LlamaIndex etc.
- Working knowledge of Graph Analytics and the relevant tools such as TigerGraph, Neo4j etc. will be a huge plus.
- Working experience in Wholesale Credit Risk (Lending or Counterparty) analytics is not a must but a plus.
- Excellent analytic ability and problem solving skills.
- Excellent communication and interpersonal skills, be organized, detail oriented, and adaptive to matrix work environment
Job Family Group:
Decision ManagementJob Family:
Specialized Analytics (Data Science/Computational Statistics)Time Type:
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