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Lead Data Scientist; Model Developer

Remote / Online - Candidates ideally in
England, UK
Listing for: Capital One UK
Full Time, Remote/Work from Home position
Listed on 2026-07-10
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 62000 GBP Yearly GBP 62000.00 YEAR
Job Description & How to Apply Below
Position: Lead Data Scientist (Model Developer)

Salary: £62, per year

Requirements
  • We are looking for strong experience developing and deploying deep learning models, particularly for sequential data such as time series or language models.
  • We need a proven track record of leading model development, including setting technical direction, project management, stakeholder communication, and mentoring junior team members.
  • We require experience producing and maintaining reliable, maintainable code in SQL and Python in a team setting, including code reviews and software engineering best practices.
  • We are looking for hands‑on experience with modern machine learning and deep learning frameworks such as PyTorch, Tensor Flow, or Hugging Face Transformers, including training models on GPUs or GPU clusters.
  • We need experience working with structured and unstructured data, such as text, logs, or time series, and familiarity with tokenisation techniques.
  • We require a strong understanding of probability, statistics, machine learning, and large dataset manipulation.
  • We value a drive for continuous learning and the ability to prototype new techniques to assess value.
  • We are seeking candidates based in the United Kingdom, with the role located in Nottingham.
  • This is a permanent position.
  • We offer a hybrid working arrangement, with three days a week in our Nottingham office and remote work on Mondays and Fridays.
Responsibilities
  • We will lead the development of next‑generation deep learning approaches to advance our underwriting models and keep our core lending capabilities at the forefront of the industry.
  • We will unlock the value in non‑traditional datasets by building sophisticated neural networks such as LSTMs, RNNs, or Transformers.
  • We will transform raw, multi‑modal inputs into powerful predictive features.
  • We will collaborate with business stakeholders to prioritise initiatives and turn ideas from initial prototypes into production‑ready solutions.
  • We will use business acumen, coding, and statistical skills to navigate large volumes of data and extract actionable solutions.
  • We will work cross‑functionally on projects that support key business initiatives and drive sustainable growth.
  • We will help bridge the gap between ambitious research and development and tangible in‑market results.
  • We will contribute to the ongoing improvement of our underwriting capabilities through high‑impact customer insights.
  • We will lead and support a collaborative, enthusiastic data science team working closely with business partners.
Technologies
  • Support
  • Machine Learning
  • Py Torch
  • Python
  • SQL
  • Tensor Flow
  • Network
More

We are Capital One, a founder‑led information‑based technology company on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. Our Data Science team is collaborative, talented, and enthusiastic, and we work closely with our business partners to solve complex problems and deliver actionable insights. This permanent Lead Data Scientist role is based in our Nottingham office with a hybrid working model, including three days a week on‑site and remote work on Mondays and Fridays.

We offer strong career progression, access to Capital One University training, core benefits such as pension, bonus, generous holiday entitlement, and private medical insurance, plus flexible benefits including season‑ticket loans, cycle to work, and enhanced parental leave. Our Nottingham head office also features open‑plan work spaces, accessible facilities, a fully serviced gym, a subsidised restaurant, mindfulness and music rooms, and we are committed to diversity, inclusion, and fair, accessible hiring.

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