Data Scientist Deep Learning Practitioner

About this role

Our Data Science team focuses on developing Machine Learning and Deep Learning solutions to solve business problems and deliver actionable insights. This senior role will develop proprietary deep learning models to address critical business challenges and support advanced servicing products using Large Language Models.

• Develop new deep learning approaches to advance our underwriting models.
• Apply models to new multi‑modal data types.
• Use business acumen, coding, and statistical skills to extract actionable solutions from large data sets.
• Work cross‑functionally on projects that support key business initiatives and drive sustainable growth.

• Experience developing and deploying deep learning models for sequential data (e.g., time series, language).
• Hands‑on experience with PyTorch, Tensor Flow, or Hugging Face Transformers.
• Familiarity with pre‑training and fine‑tuning large‑scale models.
• Experience working with structured and unstructured data such as text logs or time series and tokenisation techniques.
• Strong understanding of probability, statistics, and machine learning, and familiarity with large data set manipulation.
• Experience producing reliable and maintainable code in Python with an ability to adapt to new technologies.
• Ability to communicate findings to a diverse, business‑focused audience.
• A drive for continued learning and a commitment to developing enterprise‑level solutions.

This is a permanent position based in our Nottingham or London office. We have a hybrid working model: you’ll work from the office 3 days a week (Tuesday, Wednesday, Thursday) and work from home the remaining days.

High performers will enjoy strong career progression, a generous benefits package (pension, bonus, holiday entitlement, private medical insurance), and flexible benefits such as a season‑ticket loan, cycle‑to‑work scheme, and enhanced parental leave.

We are committed to creating a level playing field and building diverse, inclusive teams that reflect our customers and communities. We welcome applications from women, the LGBTQ+ community, and ethnic minority candidates.