Associate Director of AI & Risk Modeling-Banking

About the Role:
We are a leading international commercial bank seeking a highly skilled AI/LLM (Large Language Model) specialist to join our Traded Risk Modeling team. The ideal candidate will bring deep expertise in artificial intelligence and advanced machine learning techniques, with a particular focus on LLMs, to transform and enhance our risk modeling capabilities. This role offers the opportunity to work at the forefront of innovation, leveraging cutting-edge technologies to address complex challenges in traded risk management.

Key Responsibilities:

1. AI Integration for Traded Risk Models:

   • Develop and implement AI-driven solutions to optimize and enhance traded risk modeling processes.
   • Leverage LLMs to improve data analysis, prediction accuracy, and scenario modeling for market, credit, and liquidity risks.

2. LLM-Based Insights:

   • Use LLMs for natural language processing (NLP) to analyze market data, news, and other unstructured information for risk assessment.
   • Build intelligent systems to translate unstructured risk-related data into actionable insights for decision-making.

3. Algorithm Development & Optimization:

   • Create, test, and deploy advanced AI algorithms tailored to the unique needs of traded risk management.
   • Collaborate with quantitative analysts and risk modelers to integrate machine learning techniques into existing frameworks.

4. Collaboration & Stakeholder Engagement:

   • Work closely with cross-functional teams including IT, quantitative research, and risk management to identify AI/LLM use cases.
   • Present complex AI-driven findings to senior management and stakeholders in a clear and actionable manner.

5. Innovation & Thought Leadership:

   • Stay updated with advancements in AI and LLM technologies, ensuring the bank remains at the forefront of industry innovation.
   • Provide strategic recommendations on AI adoption for broader risk management and banking processes.

Qualifications and Skills:

• Education:

  • Master’s or PhD in Computer Science, Data Science, Quantitative Finance, Mathematics, or a related field.

• Technical Expertise:

  • Strong understanding and hands-on experience with LLM frameworks (e.g., GPT, BERT, or similar).
  • Proficient in Python, TensorFlow, PyTorch, or other machine learning libraries.
  • Knowledge of NLP, generative models, and large-scale machine learning deployment.

• Financial Acumen:

  • Familiarity with traded risk concepts (market risk, counterparty credit risk,) and financial modeling.
  • Experience working in the financial services sector or with financial datasets is a strong plus.

• Soft Skills:

  • Excellent problem-solving abilities and analytical mindset.
  • Strong communication skills with the ability to translate technical findings into business context.
  • Team player with the ability to lead projects and collaborate across functions.

Preferred Experience:

• Prior experience in a financial institution, consulting firm, or technology company focused on AI/ML applications in finance.
• Demonstrated track record of developing and deploying AI solutions in risk management or related domains.