Graduate Trainee - Data Science

Programme overview

Workplace

• The role is hybrid: trainees work from home some of the time and regularly attend an office or hub to collaborate.

Graduate journey

• Develop technical expertise in data science alongside experienced professionals.
• Collaborate on real business projects, including complex problems in areas such as Economic Crime or Climate.
• Explore how data science can enhance customer experiences across Retail, Wealth, and Commercial.
• Gain hands-on experience with tools, cloud technology, generative AI, and machine learning frameworks.
• Learn the AI solution lifecycle, from ideation and model development to deployment, monitoring, and improvement.
• Analyse complex datasets using statistical analysis, machine learning, and data visualization to inform decisions.
• Work with engineers, analysts, and cross-functional teams to turn technical findings into business outcomes.
• Explore data privacy, responsible AI, and ethical considerations in work affecting customers and communities.

Entry requirements

• Have, or be on course to achieve, a 2:1 degree in a STEM subject.
• Genuine passion for data science, AI, and helping customers.
• Good problem-solving skills and an analytical approach.
• Comfort with ambiguity and championing change and innovation.
• Resilient, curious, and inquisitive.

Compensation

• The programme lists a starting salary of £42,000 and a flexible benefits package.

Programme benefits

• Trainees learn from industry experts, apply their learning, and develop technical capability through data pathways.
• The programme offers access to a global professional network and opportunities to build confidence, resilience, and professional presence.
• Participants gain experience in an organization investing in technology to improve customer experiences.

Application information

• Applicants should make only one programme application; only their first application will be accepted.
• Applications close when enough candidates have been received to fill the cohort.