Intermediate Data Scientists (SQL, Python) to support the development and deployment of ML/AI models to drive predictive insights within the banking indust

Overview:

Our banking client is seeking Intermediate Data Scientists to support the development and deployment of ML/AI models that drive predictive insights and strengthen organizational decision-making. This role is hands-on: coding, building data pipelines, researching analytical techniques, and working closely with external partners to operationalize risk-related models. This work directly supports a major risk-rating initiative and its downstream impacts.

Must-Haves:

• 3+ years in a data science/data analyst role
• Strong hands-on coding ability with SQL and Python
• Data science modelling experience, including ML/AI predictive modelling
• Experience building and deploying data pipelines
• Econometrics/economics expertise applied within analytical or modelling contexts
• Experience working with or integrating external vendor models or platforms

Nice-to-Haves:

• Experience with risk modelling or stress-testing environments
• Exposure to model development platforms (e.g., Moody’s Portfolio Studio or similar)
• Experience supporting large transformation or analytics initiatives
• Background working in medium-sized data/analytics teams
• Knowledge of financial-services data environments (not required, but helpful)

Responsibilities:

• Develop and deploy ML/AI algorithms and predictive models
• Build, test, and maintain data pipelines
• Conduct hands-on coding and analytical research (SQL, Python, econometrics, modelling)
• Collaborate with external vendors involved in model development
• Analyze downstream impacts of a major enterprise risk-rating initiative
• Support the implementation and development of a stress-testing platform
• Work closely with business stakeholders to understand processes and data requirements
• Contribute to decision-making through clear communication of complex analytical insights