Data Scientist

JOB TITLE: Data Scientist.

SALARY: £70,900pa to £107,000pa (dependent on location and experience) plus an extensive benefits package.

HOURS: 35 hours, full time.

WORKING PATTERN: Our work style is hybrid, which involves spending at least two days per week, or 40% of your time, at one of the above the listed hubs.

Why Lloyds Banking Group? Like the modern Britain we serve, we're evolving. Investing billions in our people, data and tech to transform the way we meet the ever changing needs of our 26 million customers. We're embracing collaborative, agile ways of working, to help us deliver the best outcomes for our colleagues, customers and businesses. We're growing with purpose. Join us on our journey and you will too!

Want to hear more? We are recruiting Data Scientists for the Consumer Lending business – a diverse division that includes mortgages, credit cards, loans and vehicle finance products. As a Data Scientist you'll be involved in building, developing and improving Machine Learning (ML) solutions across the range of Consumer Lending products. You'll work on different projects with a wide variety of colleagues to understand how we can apply the latest ML thinking to deliver value.

Working in our growing team enables you to get close to and understand how the business operates, how we serve our customers and the role that Data Science and ML can play in making things better for LBG and its customers – and it's this proximity to the business that sets us apart.

Your role will evolve as the team matures, so we'd love to hear from applicants who are highly motivated, curious and open to new ways of working. We're also looking for applicants with a proven background in working with large‑scale applications and data platforms.

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• Work with other Data Scientists, ML Engineers and technical SMEs to identify, develop and implement new solutions that deliver customer and business value.
  
• Run, maintain and improve a suite of Python data science models.
  
• Work closely with business teams to identify and "prove" new use cases and the value of Data Science.
  
• Promote high quality ML practices alongside maintaining an effective control environment, sharing knowledge with others and offering technical leadership or support as needed.
  
• Proactively seek opportunities to improve solutions and present concrete plans to deliver these.
  
• Deliver in line with LBG data science, model governance and risk management policies and procedures, maintaining constructive relationships with specialist colleagues in these areas.
  
• Grow your capability by pursuing and investing in personal development opportunities.
  
• Keep up-to-date with emerging developments in the Data Science, ML engineering and ML Ops fields, and proactively share findings with the team.
  

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• Strong theoretical and applied knowledge of statistical modelling and/or ML techniques.
  
• Computer science fundamentals: a clear understanding of data structures, algorithms, software design, design patterns and core programming concepts.
  
• Good understanding of SQL and prior experience of working with large data sets.
  
• Experience across the full software development lifecycle, from experimentation through to deployment of containerised Machine Learning models to a live environment, using technologies such as Docker and Kubernetes and coding in Python.
  
• Exposure to some GCP cloud tooling (e.g. Vertex AI, BigQuery) and visualisation tools such as Looker, Tableau or PowerBI is highly desirable.
  
• Ability to extract and effectively communicate key points from complex information to support business decision making.
  
• Sound understanding of and/ or enthusiasm for the Homes, Credit Cards, Transport and Loans domains and / or an understanding of the respective products, and an appreciation of the opportunities that ML provides.
  

Our focus is to ensure we are inclusive every day, building an organisation that reflects modern society and celebrates diversity in all its forms. We want our people to feel that they belong and can be their best, regardless of background, identity, or culture. We were one of the first major organisations to set goals on diversity in senior roles, create a menopause health package, and a dedicated Working with Cancer initiative. And it is why we especially welcome applications from under‑represented groups. We are disability confident. So, if you would like reasonable adjustments to be made to our recruitment processes, just let us know.

On behalf of the team: If you are excited by the thought of becoming part of our team, get in touch.

We would love to hear from you!

• Mid‑Senior level

• Full‑time

• Engineering, Information Technology, and Other

• Banking and Financial Services