Básico

Data Scientist / Statistician (Model Developer)

leicester, midlands Compañía: JR UK Cliente / Empleador: Capital One UK
Publicado: 18.05.2026
Fecha de cierre: 02.07.2026
Referencia laboral: ca59bc13ab5bcee5bb779f53158291a2

Información del puesto

Ubicación
leicester, midlands
Compañía
JR UK
Cliente / Empleador
Capital One UK
Referencia laboral
ca59bc13ab5bcee5bb779f53158291a2
Tipo de listado
Básico
Se requiere permiso de trabajo de la UE
No
Publicado
18.05.2026
Fecha de cierre
02.07.2026

Descripción del puesto

Job DescriptionNottingham Trent House (95002), United Kingdom, Nottingham, Nottinghamshire

Data Scientist / Statistician (Model Developer)

About this role
Our Data Science team focuses on the development of machine learning and AI solutions, to solve business problems and deliver actionable insights. We are a talented, collaborative and enthusiastic group, who use our expertise to make sense of complex data, working in close collaboration with our business partners. This role will primarily focus on feature engineering and insight generation from new types of data and the development of machine learning models to address critical business challenges in underwriting. 

We are interested in candidates who have experience working with Open Banking or Credit Bureau data. A deep grounding in statistics and experience of Model Risk Management is also welcomed. 

What you’ll do

  • Develop and maintain the machine learning models which define our competitive advantage in the financial services market.

  • Explore and evaluate data, using advanced feature generation and categorisation techniques,  in order to stay at the forefront of innovation.

  • Analyse tabular and non-tabular data, such as text, logs, or time series, to produce powerful new insights.

  • Consult on complex statistical test design, to efficiently learn our way into new areas of the market.

  • Use a combination of business acumen, coding and statistical skills to navigate large amounts of data and extract actionable solutions, working cross-functionally to support key business initiatives and drive sustainable growth. 

What we’re looking for

  • A strong understanding of probability, statistics, machine learning, feature extraction and familiarity with large data set manipulation.

  • Experience using deep learning models, particularly for sequential data.

  • Familiarity with Open Banking or Credit Bureau data.

  • Experience working with multi-modal data; in multiple formats from a variety of different sources.

  • Experience in producing reliable and maintainable code in Python, with an ability to adapt to new languages and technologies.

  • Experience of Model Risk Management; technical documentation, coding best practices, the importance of validation and ongoing monitoring.

  • Natural curiosity and proactive engagement with all areas of the business, with a desire to ask questions, challenge the status-quo and identify where Data Science can add value.

  • Ability to communicate findings to a diverse business focused audience, influencing others in both verbal and written form.

  • A drive for continued learning through an internal and external focus, in order to develop enterprise and industry leading  solutions.

We are committed to creating a level playing field and seek to create teams that are representative of our customers and the communities we serve.  We’d love to hear from you if you identify with a typically under-represented group in our industry and are particularly keen to hear from women, the LGBTQ+ community and ethnic minority candidates.

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.

What you should know about how we recruit
We pride ourselves on hiring the best people, not the same people. Building diverse and inclusive teams is the right thing to do and the smart thing to do. We want to work with top talent: whoever you are, whatever you look like, wherever you come from. We know it’s about what you do, not just what you say. That’s why we make our recruitment process fair and accessible. And we offer benefits that attract people at all ages and stages.

We also partner with organisations including the Women in Finance and Race At Work Charters, Stonewall and upReach to find people from every walk of life and help them thrive with us. We have a whole host of internal networks and support groups you could be involved in, to name a few:

  • REACH – Race Equality and Culture Heritage group focuses on representation, retention and engagement for associates from minority ethnic groups and allies

  • OutFront – to provide LGBTQ+ support for all associates

  • Mind Your Mind – signposting support and promoting positive mental wellbeing for all

  • Women in Tech – promoting an inclusive environment in tech

  • EmpowHER - network of female associates and allies focusing on developing future leaders, particularly for female talent in our industry

Capital One is committed to diversity in the workplace.

If you require a reasonable adjustment, please contact   All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.

For technical support or questions about Capital One's recruiting process, please send an email to

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


Who We Are
At Capital One, we're building a leading information-based technology company. Still founder-led by Chairman and Chief Executive Officer Richard Fairbank, Capital One is on a mission to help our customers succeed by bringing ingenuity, simplicity, and humanity to banking. We measure our efforts by the success our customers enjoy and the advocacy they exhibit. We are succeeding because they are succeeding.
Guided by our shared values, we thrive in an environment where collaboration and openness are valued. We believe that innovation is powered by perspective and that teamwork and respect for each other lead to superior results. We elevate each other and obsess about doing the right thing. Our associates serve with humility and a deep respect for their responsibility in helping our customers achieve their goals and realize their dreams. Together, we are on a quest to change banking for good.

Habilidades

apply blended learning apply for research funding apply research ethics and scientific integrity principles in research activities build recommender systems Business Analytics Business Intelligence collect ICT data communicate with a non-scientific audience Computational Biology Computer Simulation conduct research across disciplines create data models Data Engineering data ethics Data Mining Data Models data quality assessment Data Science data visualisation software define data quality criteria deliver visual presentation of data demonstrate disciplinary expertise design database in the cloud design database scheme develop data processing applications develop professional network with researchers and scientists Digital Curation disseminate results to the scientific community draft scientific or academic papers and technical documentation empirical analysis establish data processes evaluate research activities execute analytical mathematical calculations Hadoop handle data samples Healthcare Analytics image recognition implement data quality processes increase the impact of science on policy and society information categorisation Information Extraction integrate gender dimension in research integrate ICT data interact professionally in research and professional environments interpret current data LDAP LINQ make data-driven decisions manage data manage data collection systems manage findable accessible interoperable and reusable data manage ICT data architecture manage ICT data classification manage intellectual property rights manage open publications manage personal professional development manage research data Marketing Analytics mathematical modelling MDX mentor individuals multidisciplinary research N1QL normalise data online analytical processing operate open source software perform data cleansing perform data mining perform project management perform scientific research promote open innovation in research promote the participation of citizens in scientific and research activities promote the transfer of knowledge publish academic research quantitative analysis query languages report analysis results Research Design resource description framework query language Scientific Computing scientific literature Social Network Analysis SPARQL speak different languages State Estimation statistical modeling techniques Statistics synthesise information teach in academic or vocational contexts think abstractly Unstructured Data use data processing techniques use databases use spreadsheets software visual presentation techniques write scientific publications XQuery

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