Applied AI ML Director (Basé à London)

As a Director in our Corporate Investment Banking (CIB) Applied AI team, you will lead the charge in developing innovative AI solutions that propel our Markets business forward. You will work closely with software engineers, business stakeholders, and AI practitioners to deliver transformative solutions that enable our business to scale and thrive. We are seeking a technical leader who is passionate about leveraging data and artificial intelligence to drive meaningful, real-world change.

Job responsibilities:

• Lead the formulation and development of AI solutions to tackle complex challenges in Markets Operations, ensuring alignment with business objectives.
• Oversee the design, development, and deployment of robust, scalable, and reusable machine learning models and systems that deliver measurable business impact.
• Actively contribute to coding efforts, ensuring high technical standards and best practices are maintained across all projects.
• Collaborate with engineering and business teams to seamlessly integrate AI services into strategic systems and processes, enhancing operational efficiency.
• Work with business partners to redefine processes and controls for an AI-first Operations business, driving innovation and efficiency.
• Establish comprehensive evaluation frameworks to assess model performance and drive continuous improvement in alignment with business goals.
• Deepen your understanding of the Markets business to identify opportunities for AI-driven innovation and deliver practical, impactful solutions.
• Lead, mentor, and inspire a team of AI practitioners, fostering a culture of excellence, innovation, and continuous learning.

Required qualifications, experience, and skills:

• Master’s or higher qualification in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related highly quantitative field.
• Extensive experience in leading and managing high-performing AI or data science teams.
• Deep understanding of fundamental machine learning approaches and practical experience with statistical data analysis and experimental design.
• Proven track record of developing and deploying data science and ML capabilities in production at scale.
• Strong experience with Python programming and common ML frameworks (e.g., PyTorch, Pandas, NumPy) and MLOps platforms (e.g., SageMaker).
• Exceptional verbal and written communication skills, with the ability to convey complex technical concepts to diverse audiences.
• Demonstrated ability to work effectively on multi-disciplinary teams with diverse backgrounds.

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