Data Scientist

Job Summary Join us as a Data Scientist

• Youll design and implement data science tools and methods which harness our data in order to drive market leading purposeful customer solutions
• Well look to you to actively participate in the data community to identify and deliver opportunities to support the banks 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
• We're offering this role at associate level

Responsibilities As a Data Scientist, youll 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. Well 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.

• 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 Youll need a strong academic background in a STEM discipline such as Mathematics, Physics, Engineering or Computer Science. Youll have experience with statistical modelling and machine learning techniques.

Well also look for financial services knowledge, and an ability to identify wider business impact, risk or opportunities and make connections across key outputs and processes. You will nedd an experience of 4+ years in the below skillset.

Youll also demonstrate:

• Agentic AI LLM ExpertiseProficiency in agentic frameworks like LangGraph, LangChain, LangFuse, MCP; strong understanding of LLMs, transformer architectures, and traditional NLP techniques for building intelligent, autonomous AI systems.
• Technical Cloud SkillsExpert in Python programming and libraries (Pandas, NumPy, scikit-learn); hands-on experience with cloud platforms for model training and deployment; tech-savvy with distributed systems and web technologies like Node.js, React.js.
• Machine Learning FundamentalsDeep knowledge of statistical concepts, linear algebra, and calculus for optimization; skilled in predictive modeling, time series analysis, deep learning, and neural networks for robust data-driven solutions.
• LLM Operations Domain KnowledgeAbility to manage and operationalize large language models; deploy models on AWS SageMaker, Google AI Platform, IBM Watson; retail banking insights and distributed systems understanding are valuable additions.

Hours 45