At a Glance
- Tasks: Lead data science and AI initiatives to modernise analytics for financial stability.
- Company: Join the Bank of England, a key player in the financial sector.
- Benefits: Competitive salary, professional development, and a chance to shape the future.
- Other info: Opportunity to lead multidisciplinary teams and influence organisational change.
- Why this job: Make a real impact on data-driven decision-making in a dynamic environment.
- Qualifications: Expertise in data science, machine learning, and cloud technologies required.
The predicted salary is between 63000 - 77000 £ per year.
WRK digital are proud to be working with the
Bank of England , who are growing their presence in Leeds!!
We are looking for an experienced data scientist to lead and help deliver an ambitious agenda on data science and AI across the directorate.
This is a new cross-directorate role and will help delivery of data science-driven and AI-driven analytics.
This is an exciting opportunity to play a key role in modernising their use of data and analytics to support financial stability analysis, working in conjunction with the relevant analytical divisions within the directorate.
The person who takes on this role will have a real opportunity to shape how things are done, making a big difference now and in influencing the vision for the future.
- Roles and Responsibilities
- Develop & implement cloud based analytical solutions.
- Build the Banks' AI and data science capabilities.
- Provide leadership of key policy projects deploying the latest data science and AI tools.
- As Lead Data Scientist in FSSR, support the professional development of staff.
- Lead and deliver FSSR’s Data & AI strategy as part of the broader DGFS agenda
- Role Requirements
- Advanced technical expertise in data science, machine learning or data engineering, including experience with Python and/or R.
- Strong understanding of cloud-based technologies and solutions (Azure and Databricks preferred), Dev Ops practices and API‑driven architectures.
- Experience of large language models (LLMs), generative AI technologies including AI agents and their practical applications.
- Proven experience leading analytical projects that leverage large and complex datasets, applying data science, machine learning and AI techniques to derive actionable insights and support policy.
- Experience delivering business change and production‑ready pipelines through new data and technology systems. A strong understanding of organisational data and AI transformation.
- Ability to lead multidisciplinary technical projects and teams, with the ability to set strategy and technical direction, manage staff during a project and deliver results in ambiguous, fast‑moving environments.
Unfortunately this role does not offer sponsorship at this time.
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Senior Manager, Data Science & AI in Leeds employer: WRK digital
WRK digital is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those looking to make a significant impact in the tech industry. With a focus on employee growth, we offer ample opportunities for professional development and collaboration across internationally distributed teams. Our commitment to best practices in frontend engineering ensures that you will be part of a forward-thinking organisation that values your contributions and encourages creativity.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Manager, Data Science & AI in Leeds
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We think you need these skills to ace Senior Manager, Data Science & AI in Leeds
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
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✨Brush Up on Your Statistics
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✨Get Comfortable with Python and R
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✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
