The Applied AI & ML ā Market Operations team is dedicated to transforming and optimising operational processes within Corporate & Investment Banking (CIB) Markets Operations. We leverage advanced artificial intelligence and machine learning techniques to solve complex business challenges, automate workflows, and deliver impactful solutions that drive efficiency and accuracy across CIB.
As an Applied AI & ML Associate in the Market Operations team, you will play a key role in designing, developing, and deploying AI/ML solutions that directly support and enhance Markets Operations within CIB. You will work closely with business stakeholders and technology partners to understand operational pain points, translate requirements into technical solutions, and ensure successful implementation and adoption of AI-driven tools.
Job Responsibilities
Contribute towards the development and implementation of advanced machine learning models and algorithms to address complex operational challenges.
Develop and deploy AI/ML models and solutions to address specific operational challenges in Markets Operations (e.g. process automation, anomaly detection, document intelligence, workflow optimisation)
Architect and oversee the deployment of generative AI applications and agents to automate and enhance business processes.
Build and maintain production-grade AI/ML applications and tools tailored to Market Operations needs
Monitor, evaluate, and continuously improve the performance of deployed models and solutions
Analyse large and complex datasets to identify trends, inefficiencies, and opportunities for automation or improvement
Collaborate with Market Operations subject matter experts to gather requirements, validate solutions, and measure impact
Document methodologies, results, and best practices to support knowledge sharing and solution scalability
Stay up to date with the latest AI/ML advancements and apply relevant techniques to business problems
Required Qualifications, Capabilities, and Skills
BSc/MSc in Data Science, Computer Science, Artificial Intelligence, or a closely related field (or equivalent experience)
Strong foundation in AI/ML concepts and practical experience with data analysis, feature engineering, and model development
Experience working with large, complex datasets and applying statistical analysis
Hands-on experience training, deploying, and maintaining machine learning models in production environments
Proficiency in Python and relevant AI/ML libraries (e.g. scikit-learn, TensorFlow, PyTorch)
Experience with MLOps practices and tools for managing the end-to-end machine learning lifecycle
Experience building and deploying Generative AI applications, including familiarity with LLMOps (Large Language Model Operations)
Exposure to cloud platforms (e.g. AWS, GCP, Azure)
Demonstrated problem-solving skills and ability to work independently or in small teams
Ability to communicate technical concepts clearly to business stakeholders and non-technical audiences
Preferred Qualifications, Capabilities, and Skills
PhD in Data Science, Computer Science, Artificial Intelligence, or a related field
Experience in financial services, banking, or Markets Operations environments