Partnering with mission-driven entrepreneurs to build Rocky Mountain technology companies of impact, utility, and value.

CIB Applied AI & Machine Learning Associate - Digital & Platform Services Operations

About the role

As a member of the CIB Applied AI/ML for Operations team, you will have the unique opportunity to be a critical player in our firm-wide efforts to shape the future of banking. Crucial to this is helping to transform Operations teams, where you will have a direct impact on the behind-the-scenes management and functioning of the bank's corporate and investment banking services.

You will be a key member of a cross-functional team of data scientists, operations experts, engineers, designers and product managers to design, develop and deploy scalable machine learning products. Our vision is to create products that transform how operations teams service our clients, deliver measurable impact and have the potential for commercialization.

Finance background is not a must-have. If you get as excited about machine learning theory as you get about Python development, we’d love to speak with you.

In this role, you will:

• Interact with very large datasets in the financial domain currently not available anywhere else
• Write production-ready code and work with tech teams to ensure your machine learning solution is deployable at scale across multiple lines of business
• Develop products that can change how corporate and investment banking is done today

Responsibilities

• Research and develop innovative ML based solutions to some of Operations' hardest problems
• Build robust Data Science capabilities which can be scalable across multiple business use cases
• Collaborate with software engineering team to design and deploy Machine Learning services that can be integrated with strategic systems
• Research and analyse 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

Required Technical Qualifications And Experience

• Masters degree in a quantitative or computational discipline
• Commercial experience developing and deploying Data Science and ML capabilities in production at scale
• Strong Python development and debugging skills
• Experience with Natural Language Processing (NLP)
• Experience with machine learning frameworks (pytorch, tensorflow) and data science packages (examples: Scikit-Learn, NumPy, SciPy, Pandas, statsmodels)
• Ability to to work both individually and in collaboration with others
• Curiosity, attention to detail and interest in complex analytical problems
• Results-driven mindset and client focus
• Ability to work in agile cross-functional teams

Nice to Have

• Ability to design intrinsic and extrinsic evaluations of a model's performance which are aligned with business goals
• Ability to work with non-specialists in a partnership model, conveying information clearly and creates a sense of trust with stakeholders
• Experience with inference, training and deployment of Large Language Models
• Experience with big-data technologies such as Spark