Success in the role will come from designing interfaces and interaction patterns that help people understand, trust, and effectively use AI systems. This includes participating in user research, prototyping intelligent interfaces, validating usability, and collaborating with data scientists, product owners, and engineers.

As AI becomes central to financial services—from digital assistants to automated decision-making—thoughtful, well-designed AI interactions is critical. This position in AI Design will ensure our internally designed solutions are not only smart, but also inclusive, transparent, and usable—driving trust and value for customers and colleagues.

About the job

Who we are

The new AI Design team sits in the Data Science group within Retail Banking Transformation Analytics – we are focused on applying science (from fine-tuned linear models through to machine learning and AI) to our petabytes of data to uncover insights about our customers and their financial behaviors, assess risk and opportunities, drive scalable growth, surprise and delight our customers with bespoke experiences in branch and online, and improve the digital banking experience. 

We work with key business leaders and decision makers to refine and solve problems by mining, analyzing, and modeling data to provide insights that drive change. The day-to-day includes exploratory analysis to understand data structures and relationships, working closely with our business partners to build insight into new problems, research to refine a methodology, cranking out lightning-fast machine learning code to create a model that predicts trends and automates validation, collaborating with cross-functional teams, or visualizing and sharing their results with executives. Our work as innovators means that we are approaching new problems on novel (and potentially unstable) data and there is no playbook for best practice; instead, we rely on our understanding of applied statistics and incrementality, alongside industry knowledge of trends in customer channel behavior and a toolbox of machine learning approaches/algorithms to resolve the tension between complexity, scope, and explainability.

The ideal data scientist in our squad is comfortable working with a variety of partners (business verticals, IT, data engineering, risk...etc.) and data (structured, unstructured, streaming) in a shared code repository utilizing multiple programming languages and frameworks to deliver state-of-the-art frameworks, analytics and models in an agile environment. 

We are from a range of backgrounds - mathematicians, statisticians, economists, engineers, computer scientists, physicists, financiers, and of course data scientists – but we are all skilled in research methods, and are obsessed with our customers, financial projections, data science, research, AI, programming, clean and powerful data visualizations to communicate our ideas, and collaborating to find the best approach to emerging questions.

Who you are

• You are a customer-centered thinker who prioritizes transparency/explainability and designs with the end user in mind to create intuitive, accessible tools which solve real problems.

• You are an AI translator, able to bridge the gap between raw model capabilities and practical, business-facing applications.

• You are endlessly curious, a lifelong learner who is driven to keep pace with the latest technologies and applications.

• You are passionate about smooth integration of systems, and have a vision beyond isolated scripts and demos for your products to fit securely and reliably into existing systems and tech stacks.

• You are able to explain your logical and structured thinking/processes in different ways to different people while maintaining the honesty and integrity of your work.

• You are mission driven, striving to connect your technical work with the broader purpose of the bank, working to help our people and businesses prosper.

• You are impact focused whilst being aware of your responsibility to design with fairness and inclusivity in mind to mitigate amplification of bias.

• You love being part of a fast-moving supportive team and welcome feedback to learn.

• You are organized and able to document what you produce.

• You are comfortable with ambiguity and charting a path through quantitative analysis.

Examples of potential work
Early use cases include development of an LLM Reporting Assistant, an Agent Assist Chat Tool, and Banker Procedure Support Platform. 

Role and Responsibilities

• Develop frontend and backend components of AI-driven apps using modern web frameworks and APIs.

• Integrate LLMs and ML models into business applications using APIs.

• Build workflows and interfaces that support natural language queries, report generation, summarization, or recommendation systems.

• Implement RAG pipelines using vector stores and enterprise content sources.

• Ensure performance, security, and scalability of cloud-native AI applications you build.

• Collaborate with prompt engineers to test and refine LLM outputs in real-time user contexts.

• Instrument applications for observability, error tracking, and user feedback to drive continuous improvement.

• Stay current with emerging AI/LLM app frameworks, developer tools, and responsible AI best practices.

Technical Skills

• Basic understanding of how LLMs, NLP, or AI decision systems function.

• Preferred, hands-on experience designing prompts for GPT-4, Claude, or Gemini and exposure to Snowflake Cortex.

• Strong communication and collaboration skills across design, product, and technical teams.

• Understanding of enterprise guardrails for hallucination detection, fallback, and escalation

• Interest in ethical AI, human-centered design, and user trust in automated systems.

• Ability to translate complex technical behaviors into clear, helpful user experiences.

• A growth mindset and a willingness to experiment and learn in a fast-evolving space.

• Master’s degree in a quantitative area (Computer Science preferred) or a terminal degree in any field.

• 3 years of relevant professional (or research) experience 

At Santander, we value and respect differences in our workforce and strive to increase the diversity of our teams. We encourage everyone to apply.