Senior Data Scientist | S4 | Chief Data & AI Office
Listed on 2026-08-28
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IT/Tech
AI Engineer (Applied/Software), Data Scientist, Machine Learning/ ML Engineer, Data Analyst
Senior Data Scientist | S4 | Chief Data & AI Office | Milton Keynes Country:
United Kingdom
Santander () is evolving from a global, high-impact brand into a technology-driven organisation, and our people are at the heart of this journey. Together, we are driving a customer-centric transformation that values bold thinking, innovation, and the courage to challenge what’s possible.
This is more than a strategic shift. It’s a chance for driven professionals to grow, learn, and make a real difference.
Our mission is to contribute to help more people and businesses prosper. We embrace a strong risk culture and all our professionals at all levels are expected to take a proactive and responsible approach toward risk management.
The Chief Data & AI Office (CDAIO) at Santander is responsible for setting the strategic direction for data, analytics, and artificial intelligence across the organisation. It ensures that data is managed as a trusted enterprise asset and that advanced technologies are applied responsibly, securely, and effectively to create value for customers and the business.
THE DIFFERENCE YOU MAKEThe Chief Data & AI Office (CDAIO) is looking for a Senior Data Scientist based out of Milton Keynes.
As a Senior Data Scientist, you will work with vast datasets to develop models that solve real-world problems, collaborate with talented colleagues across disciplines, and connect with the broader AI community to push scientific and practical boundaries.
We’re shaping the way we work through innovation, cutting-edge technology, collaboration and the freedom to explore new ideas. To succeed in this role, you will be responsible for:
Research, design, and implement advanced AI algorithms (ML, DL, NLP, and beyond) to solve complex problems.
Leading the development and implementation of advanced analytics solutions, including predictive modelling, machine learning and statistical analysis to solve complex business problems.
Translate business challenges into scientific problem statements and build impactful ML/AI prototypes and models that deliver business impact.
Work with large-scale structured and unstructured data to develop models that are accurate, fair, and sustainable.
Collaborate with Data Engineers, ML Ops Engineers, Product Owners, and Business Stakeholders to deploy solutions into production.
Contribute to AI best practices, model governance, and responsible AI frameworks.
Stay current with the latest AI research and integrate relevant tools and techniques.
Communicate insights and results clearly to both technical and non-technical audiences.
Foster collaboration with academia and the global AI community to bring cutting-edge research into Santander.
Our people are our greatest strength. Every individual contributes unique perspectives that make us stronger as a team and as an organisation. We’re enabling teams to go beyond by valuing who they are and empowering what they bring.
The following requirements represent the knowledge, skills, and abilities essential for success in this role. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Professional ExperienceIdeally, 6-8 years of experience working with vast datasets and developing models. (Required).
Undergraduate degree in Computer Science or a related field, or equivalent work experience supported by professional certification/licences. (Required).
English. (Required)
Knows the existing state-of-art advance analytics and analyses their different business applications. (Required).
Participates in the design and development of data mining applications. (Required).
Monitors the operation and performance of machine learning projects. (Required).
Conducts walkthroughs and monitors the quality of development activities. (Required).
Provides management reports that identify potential business performance problems. (Required).
Knowledge of the how's and why's of preparing and justifying business cases and value propositions; ability to justify business expenditures by identifying cost, benefits, ROI, opportunities, and risks.…
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