At a Glance
- Tasks: Lead data science and AI initiatives to modernise financial stability analysis.
- Company: Join the Bank of England, a key player in financial stability.
- Benefits: Competitive salary, excellent benefits, and flexible working arrangements.
- Other info: Exciting opportunity for career growth in a dynamic environment.
- Why this job: Shape the future of data analytics in a prestigious institution.
- Qualifications: Advanced expertise in data science, machine learning, and cloud technologies.
The predicted salary is between 97920 - 110160 £ per year.
Location: Leeds (2-3 days a week)
Employment Type: Permanent
Status: Actively Hiring
Salary: £97,920-£110,160 + Excellent Benefits
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 FSSRs 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), DevOps 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.
Senior Manager of Data Science in Leeds employer: Stryker Corporation
Stryker Corporation is an exceptional employer that fosters a dynamic and inclusive work culture, offering employees the chance to thrive in a remote setting while being part of a leading medical communications team. With a strong emphasis on professional development and growth opportunities, employees are encouraged to enhance their skills and advance their careers, all while contributing to meaningful projects that impact healthcare globally.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Manager of Data Science in Leeds
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We think you need these skills to ace Senior Manager of Data Science 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
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
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Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨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.
