Graduate Trainee - Data Science
- Develop deep technical expertise in data science, working alongside experienced professionals across teams such as Climate Analytics, Fraud, Financial Crime, Retail Banking, and Innovation
- Gain a strong understanding of how data science can enhance customer experiences
- Gain hands-on experience with key tools and technologies, develop models using state-of-the-art cloud technology, and learn how to effectively build models utilising generative AI and machine learning frameworks
- Learn the full lifecycle of developing AI solutions-from ideation and model development to deployment, monitoring, and continuous improvement
- Work with large and complex datasets, applying statistical analysis, machine learning, and data visualisation techniques to uncover insights and inform strategic decisions
- Collaborate with Engineers, Analysts, and cross-functional teams, developing your communication and problem-solving skills to effectively translate technical findings into actionable business outcomes
- Explore ethical considerations in data science, with a strong focus on data privacy, responsible AI, and doing what's right for our customers and communities
- Learn from industry experts and immediately apply your learnings
- Accelerate your technical capability
- Enrich your learning with full access to our data pathways
- Expand your global professional network
- Grow your confidence, build your resilience, and elevate your presence and personal brand
- Experience first-hand what it's like working in a purpose-driven organisation that's investing in technology to deliver first-class customer experiences
- To have, or be on course to achieving, a 2:1 in your degree in a STEM subject
- A genuine passion for data science, AI, and helping customers
- Good problem-solving skills with an analytical approach
- To be comfortable with ambiguity and championing change and innovation in an evolving world
- To be resilient, curious, and inquisitive
35 Job Posting Closing Date:
Job Posting Closing Date is not yet published. Ways of Working:Remote First
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