- You'll design and implement data science tools and methods which harness our data in order to drive market leading purposeful customer solutions

- We'll look to you to actively participate in the data community to identify and deliver opportunities to support the bank's strategic direction through better use of data

- This is an opportunity to promote data literacy education with business stakeholders supporting them to foster a data driven culture and to make a real impact with your work

What you'll do :

As a Data Scientist, you'll bring together statistical, mathematical, machine-learning and software engineering skills to consider multiple solutions, techniques and algorithms to develop and implement ethically sound models end-to-end.

We'll look to you to understand the needs of business stakeholders, form hypotheses and identify suitable data and analytics solutions to meet those needs in order to support the achievement of our business strategy.

You'll also be :

- Using data translation skills to work closely with business stakeholders to define detailed business questions, problems or opportunities which can be supported through analytics

- Applying a software engineering and product development lens to business problems, creating, scaling and deploying software driven products and services

- Working in an Agile way within multi-disciplinary data and analytics teams to achieve agreed project and scrum outcomes

- Selecting, building, training and testing machine learning models considering model valuation, model risk, governance and ethics, making sure that models are ready to implement and scale

- Iteratively building and prototyping data analysis pipelines to provide insights that will ultimately lead to production deployment

The skills you'll need :

- You'll need at least four years of experience in Designing, developing, and deploying Machine Learning (ML) and Deep Learning (DL) models into production environments.

- You'll need experience in building advanced AI applications leveraging CNNs, RNNs, Transformers, and Agentic AI frameworks while Developing and optimizing Retrieval-Augmented Generation (RAG) and other Agentic AI solutions.

- You'll also need programming experience in Python and frameworks like TensorFlow or PyTorch, PySpark, data pipelines, ETL processes, and model monitoring with familiarity with cloud platforms like AWS, Azure, GCP for ML/DL deployment.

- Participation history on Kaggle or other data science competitive platforms will be preferred.

You'll also demonstrate :

- The ability to use data to solve business problems from hypotheses through to resolution

- Experience using programming language and software engineering fundamentals

- Develop and maintain MLOps, DLOps Ops pipelines

- Collaborate with cross-functional teams to deliver scalable data-driven solutions.

- Conduct research and stay updated on emerging trends in ML, DL, and AI technologies.

- Experience in synthesising, translating and visualising data and insights for key stakeholders

- Experience of exploratory data analysis