Lead Data Scientist (Model Developer) / Deep Learning Practitioner in Nottingham

Our Data Science team focuses on the development of Machine Learning and Deep Learning solutions, to solve business problems and deliver actionable insights. We are a talented, collaborative and enthusiastic group, who use our expertise to derive insights from complex data, working in close collaboration with our business partners. This role will focus on leading the development of proprietary deep learning models in order to enhance our existing underwriting capabilities. By utilizing a mix of new and existing data, you will identify ways to improve predictive power and generate high‑impact customer insights.

What you’ll do:

• Lead the development of next generation deep learning approaches to advance our current underwriting models, to ensure that our core lending capabilities remain at the forefront of the industry.
• Unlock the value in non‑traditional datasets by building sophisticated neural networks (e.g. LSTMs, RNNs, or Transformers).
• Find novel ways to transform raw, multi‑modal inputs into powerful predictive features.
• Collaborate with business stakeholders to prioritise initiatives.
• Bridge the gap between ambitious R&D and tangible in‑market results, driving ideas from initial prototypes through to production.
• Use a combination of business acumen, coding and statistical skills to navigate large amounts of data and extract actionable solutions.
• Work cross‑functionally on projects that support key business initiatives and drive sustainable growth.

What we’re looking for:

• Strong experience developing and deploying deep learning models, particularly for sequential data (e.g. time series or language models).
• A proven track record leading model development, including setting the technical direction, project management, stakeholder communications, and mentoring junior members of the team.
• Experience producing and managing reliable and maintainable code in SQL/Python in a team setting, including code reviews and setting software engineering best practices.
• Hands‑on experience with modern Machine/Deep Learning frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers, including training deep learning models on GPUs or GPU clusters.
• Experience working with structured and unstructured data, such as text, logs, or time series and tokenisation techniques.
• A strong understanding of probability, statistics, machine learning and familiarity with large data set manipulation.
• A drive for continued learning through an internal and external focus, and an ability to prototype new techniques to assess value.

Where and how you’ll work:

This is a permanent position based in our Nottingham office. We have a hybrid working model, so you’ll be based in our office 3 days a week on Tuesdays, Wednesdays and Thursdays, and can work from home on Monday and Friday. Many of our associates have flexible working arrangements, and we’re open to talking about an arrangement that works for you.

What’s in it for you:

Bring us all this – and you’ll be well rewarded with a role contributing to the roadmap of an organisation committed to transformation. We offer high performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes (and appropriate external providers). Immediate access to our core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance – with flexible benefits available including season‑ticket loans, cycle to work scheme and enhanced parental leave. Open‑plan workspaces and accessible facilities designed to inspire and support you. Our Nottingham head‑office has a fully‑serviced gym, subsidised restaurant, mindfulness and music rooms.

Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please contact ukrecruitment@capitalone.com. All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.