Applied AI & Machine Learning Associate – Digital & Platform Services Operations

Applied Ai & Machine Learning Associate

Join us to shape the future of banking through cutting-edge AI and machine learning. You'll collaborate with a dynamic team of data scientists, engineers, and product managers to create impactful products for our operations teams. This is your opportunity to work on unique financial datasets and deliver solutions that make a measurable difference. We value your curiosity and passion for both theory and hands-on development. Discover career growth and the chance to influence how banking is done.

As an Applied AI & Machine Learning Associate in Digital & Platform Services Operations, you will design, develop, and deploy machine learning products that enhance our corporate and investment banking services. You'll work closely with cross-functional teams to deliver scalable solutions and drive operational transformation. Your contributions will directly impact how we serve clients and manage behind-the-scenes operations. We foster a collaborative environment where your ideas and expertise are valued.

Job Responsibilities:

• Research and develop innovative machine learning solutions for complex operational challenges
• Build robust data science capabilities scalable across multiple business use cases
• Collaborate with software engineering teams to design and deploy machine learning services
• Analyze large financial datasets using statistical and machine learning techniques
• Communicate AI capabilities and results to technical and non-technical audiences
• Document methodologies, techniques, and processes
• Write production-ready code and ensure solutions are deployable at scale
• Develop products that transform corporate and investment banking operations
• Work in agile, cross-functional teams to deliver impactful solutions

Required Qualifications, Capabilities, and Skills:

• Master's degree in a quantitative or computational discipline
• Hands-on experience developing and deploying data science and machine learning capabilities in production
• Proficiency in Python development, debugging, and maintenance
• Experience with Natural Language Processing (NLP)
• Familiarity with machine learning frameworks (e.g., PyTorch, TensorFlow) and data science packages (e.g., Scikit-Learn, NumPy, SciPy, Pandas, statsmodels)
• Ability to work independently and collaboratively
• Strong attention to detail and interest in analytical problem-solving
• Results-driven mindset with a client focus
• Ability to thrive in agile, cross-functional teams

Preferred Qualifications, Capabilities, and Skills:

• Ability to design model evaluations aligned with business goals
• Experience partnering with non-specialists and building stakeholder trust
• Experience with inference, training, and deployment of Large Language Models
• Experience building generative AI solutions
• Experience developing scalable machine learning systems
• Familiarity with big-data technologies such as Spark