Applied AI Senior Associate - Cross Functional

As an Applied AI Senior Associate within the Corporate and Investment Banking (CIB) Cross-Functional Applied AI/Machine Learning team, you will have the unique opportunity to shape the future of banking. You will play a crucial role in our company-wide efforts to revolutionize how cross-functional and operations teams function, directly influencing the management and operation of the bank's corporate and investment banking services. You will work in collaboration with a cross-functional team of data scientists, subject matter experts, and Machine Learning engineers to design, develop, and implement scalable machine learning solutions. Your contributions will aid in creating products that transform the way the firm operates, delivering measurable impact, and possessing the potential for commercialization.

No finance background? No worries. If you're passionate about machine learning theory and Python development, we're eager to connect with you.

Job responsibilities

• Interact with very large datasets from different businesses in the financial domain currently not available anywhere else.
• Write production-ready code and work with tech teams to ensure your ML solution is deployable at scale across multiple lines of business.
• Develop products that can change how corporate and investment banking is done today.
• Research and develop innovative ML based solutions to some of cross-functions and operations hardest problems.
• Build robust data science capabilities which can be scaled across multiple business use cases.
• Collaborate with software engineering teams to design, deploy, and maintain production-grade ML models that can be integrated with strategic systems.
• Research and analyze large data sets using a variety of statistical and machine learning techniques.
• Communicate AI capabilities and results to both technical and non-technical audiences.
• Document approaches taken, techniques used, and processes followed to comply with industry regulation.

Required Technical Qualifications and Experience

• Masters degree or PhD in a quantitative or computational discipline
• Considerable commercial experience in line with a capable individual contributor; developing and deploying data science and ML capabilities in production at scale.
• Strong Python development and debugging skills. Capable to develop high quality reusable code that can be leveraged from a larger group of data scientists to solve a broad spectrum of business use cases.
• Ability to work both individually and in collaboration with others, and to mentor more junior team members.
• Ability to work in agile cross-functional and operations teams and drive deliverable outcomes.
• Ability to work with non-specialists in a partnership model, conveying information clearly and creates a sense of trust with stakeholders.

Preferred qualifications, capabilities and skills

• Experience with deep learning frameworks (pytorch, tensorflow) 
• Experience with big-data technologies (Spark, Hadoop) or distributed computation frameworks (Dask, Modin)
• Hands on experience with Natural Language Processing (NLP) and Large Language Models (LLMs)
• Experience of creating and deploying microservices
• Knowledge of MLOps concepts (CI/CD, versioning, reproducibility, observability) and development best practices