AWM Quant Modelling- Senior Associate

• dentify and evaluate use cases for data science to enhance risk analytics and create business value.
• Lead the development and continuous improvement of AI/ML and statistical techniques for data validation and analytics.
• Design, pre-train, and fine-tune production-grade language models for hierarchical classification, summarization, and QA.
• Collaborate with stakeholders to deliver scalable, flexible solutions using approved AI and LLM technologies.
• Perform prompt engineering, quantization, and evaluation to optimize large language model robustness and performance.
• Analyze and onboard new, large data sets, ensuring alignment with best practice data models and architecture.
• Partner with Technology teams to optimize model performance and deployment using customized training frameworks.
• Design and implement sophisticated model serving systems leveraging distributed systems and AWS cloud.
• Contribute to the research and enhancement of risk methodologies, including sensitivity, stress, VaR, factor modeling, and Lending Value pricing.
• Support the full product development lifecycle, from defining objectives to delivering key data-driven solutions.
• Communicate complex technical concepts clearly to both technical and non-technical stakeholders.

Required Qualifications, Capabilities, and Skills

• Minimum 2 years’ work experience as a Data Scientist or in an applied AI/quantitative role, developing and deploying NLP and predictive models.
• Strong foundation in statistics, applied AI/ML techniques, and advanced problem-solving.
• Hands-on experience with distributed computing, NLP (entity recognition, text classification, summarization, QA), and LLM optimization.
• Proficiency in Python, SQL, R, PyTorch or TensorFlow, and AWS.
• Experience with frameworks such as LangChain, LangGraph, or AutoGen.
• Demonstrated ability to improve model robustness and conduct advanced statistical modeling and A/B testing.
• Detail-oriented, able to multi-task, and work independently in a fast-paced environment.
• Excellent communication and collaboration skills.
• Experience in modular programming and big data platforms.
• Bachelor’s degree in a quantitative or technology field (AI, Mathematics, Statistics, Engineering, Computer Science, or equivalent).
• Proven track record of delivering data-driven solutions in a business context.

Preferred Qualifications, Capabilities, and Skills

• Experience in financial markets in a quantitative analysis, research, or risk management role.
• Knowledge of asset pricing, VaR backtesting, and model performance testing.
• Advanced degree (Master’s or PhD) in a quantitative or technology discipline.
• Experience with model serving systems and distributed architectures.
• Familiarity with citizen developer platforms and process automation.
• Exposure to Front Office or equivalent financial roles.
  • Demonstrated ability to drive innovation and efficiency in risk analytics.