White Collar Factory (95009), United Kingdom, London, London

Lead Data Scientist – Deep Learning Practitioner

About this role

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 primarily focus on leading the development of proprietary deep learning models to address critical business challenges in underwriting. The role will also involve supporting our business partners as they develop advanced servicing products using Large Language Models.

What you’ll do

Lead the development of new deep learning approaches to advance our current underwriting models, which form the heart of our lending business. Apply these to new types of (multi-modal) data in order to stay at the forefront of innovation.

Prioritise and own the roadmap for this work. Balancing R&D with in‑market results, you will drive ideas from prototypes through to production.

Provide consultancy to our tech and product partners, to help design, develop and launch products powered by Large Language Models (LLMs). This collaboration will help provide seamless experiences for our customers and associates.

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, language) using techniques such as LSTMs or transformers.

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 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.

Familiarity with both pre‑training and fine‑tuning of large‑scale models.

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 or London 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. In London, you can heighten your mood with a run on our rooftop running track or an espresso at the Workshop Coffee café.

Posting Date: 21/11/2025

Senior (5+ years of experience)

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