Data Scientist​/Statistician; Model Developer in Mansfield

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

Data Scientist / Statistician (Model Developer)

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 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.

• Develop and maintain the machine learning models which define our competitive advantage in the financial services market.
• Explore and evaluate data, using advanced feature 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.

• 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 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.

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.

• 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 work spaces and accessible facilities designed to inspire and support you. Our Nottingham head-office has a fully-serviced gym, subsidised restaurant, mindfulness and music rooms.

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 + community and minority candidates.