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Analyst – Data Science

Data and Statistics Division (DSD) is the Bank’s centre of expertise for compilation, dissemination and publication of regulatory and statistical data, promoting innovation and quality to support analysis, policy and decision making by the Bank’s Committees, UK government departments and international organisations.

Data are collected from banks and buildings societies, credit unions, insurance companies and regulated mortgage lenders and administrators. This takes place via 35 statistical collections and over 200 regulatory collections.

We cleanse a sizeable proportion of these datasets and publish a large amount of Statistical and Regulatory data. We support the Monetary Policy Committee (MPC), Financial Policy Committee (FPC) and Prudential Regulation Authority (PRA) Board and work closely with colleagues across the Bank.

Department Overview

The Data and Statistics Division (DSD), part of the Bank’s Data and Analytics Transformation Directorate (DAT), is the division with responsibilities that span production and management of some of the Bank’s core datasets. The directorate more broadly is responsible for aspects of data management and data culture that reach into the working lives of almost all Bank staff.

This is a time of significant change as the way we collect and handle data, and compile statistics, evolves in the light of the use of new technology with DSD at the forefront. The change draws on a wide range of skills, including: data management; data science; data systems; data engineering; data modelling; operational work; and subject matter expertise in aspects of economics, statistics, banking and insurance supervision, and the UK housing and mortgage markets.

The advertised roles sit in the division’s Regulatory Data Group (RDG, and the Division’s Financial Statistics Group (FSG). The Regulatory Data Group’s primary focus is to contribute to the Bank of England core purposes and external commitments by collecting and quality assuring regulatory data. Currently, there are three main operational teams within RDG: Banking, Insurance and Household & Rates. The Financial Statistics Group’s focus is on the analysis, compilation, and publication of key statistical outputs such as monetary financial institutions’ contribution to the National Accounts, International Banking Statistics, and capital issuance.

RDG’s role is in the Insurance & Credit Unions team that works alongside the other RDG operational teams to support the delivery of and continued maintenance of the team’s regulatory data change activities and management of the plausibility checking processes of firm-level data, which includes machine learning and associated quality assurance processes. The team works closely with the Insurance Analytics Department within the PRA Insurance Division, as well as with insurance and credit union supervisors and the actuarial teams.

The FSG role involves compiling data used by the ONS and a variety of international organisations, including the Eurostat, BIS, IMF, and more, and feature in headline UK statistics such as the Gross Domestic Product, Balance of Payments, and UK Trade.

Job description

RDG is looking for a data scientist who possesses, or can develop, a high level of insurance regulatory data expertise and has the relevant skills to quality assure large volumes of data, and to implement processes to increase the breadth and improve the efficiency of that quality assurance. FSG is seeking a proactive and highly motivated individual to provide analytical input to the processes used to compile, analyse and publish the group’s high profile statistical datasets. Roles in FSG provide a good opportunity for candidates who are interested in working in a live, high profile and operational area of the Bank.

The roles on both teams are broadly similar in that both involve managing the compilation of quarterly and annual data alongside delivery improvements to both data quality and supporting tools and techniques.

During quarterly and annual data production cycles, which occupy around 40-50 per cent of our time, the successful applicant will apply statistical methods and good judgement to identify and explain unusual movements in both firm level and aggregate reported statistics. They will also contribute to the production of aggregated data published on the Bank website, and respond to requests for market information from stakeholders within and outside the Bank.

The rest of the time will be used to help develop statistical tools to improve the efficiency of the data quality checking, through the use of statistical techniques and machine learning, using both R and Python. Using these tools in line with standard methodology is one of DAT’s broader directorate objectives.

The successful applicant will work in collaboration with other data scientists, and will have the opportunity to upskill and mentor others in the team and across DAT.

This role will also offer a variety of opportunities for involvement in division-wide projects, depending on the skills and interest of the successful applicant.

The job holder will need to have:

• Strong technical and quantitative skills.
• Demonstrable experience in identifying and implementing improvements in data processes through the use of automation, with experience of handling and manipulating large volumes of data in an efficient, effective and accurate way.
• Strong demonstrable experience of using programming languages (such as R, Python and SQL) and advanced data manipulation techniques with an ability to understand their practical application in numerical analysis and data quality.
• Ability to communicate effectively, clearly, and confidently both orally and in writing.
• A high level of motivation and autonomy in their day-to-day work and when acquiring new skills and knowledge.

• A good understanding of economics, finance, and the UK insurance market would be preferable though there is plenty of scope to build up expertise in these areas.
• Experience of building relationships with stakeholders.
• Experience in designing and implementing data models, pipelines and complex coding solutions.
• Knowledge of using collaboration, version control and DevOps tools including but not limited to Jira, Confluence, Azure DevOps, Git is an added advantage.

Our Approach to Inclusion

The Bank values diversity, equity and inclusion. We play a key role in maintaining monetary and financial stability, and to do that effectively, we believe we need a workforce that reflects the society we serve.

At the Bank of England we want all colleagues to feel valued and respected, so we're working hard to build an inclusive culture which supports people from all backgrounds and communities to be at their best at work. We celebrate all forms of diversity, including (but not limited to) age, disability, ethnicity, gender, gender identity, race, religion, sexual orientation and socioeconomic status. We believe that it’s by drawing on different perspectives and experiences that we’ll continue to make the best decisions for the public.

We welcome applications from individuals who work flexibly, including job shares and part time working patterns. We've also partnered with external organisations to support us in making adjustments for candidates and employees in the recruitment process where they're needed.

For most roles where work can be carried out at home, we aim for colleagues to spend half of their time in the office, with a minimum of 40% per month. Subject to that minimum requirement, individuals and managers should work together to find what works best for them, their team and stakeholders.

Finally, we're proud to be a member of the Disability Confident scheme. You can find more information on what this means here. If you wish to apply under this scheme, you should check the box in the ‘Candidate Personal Information’ under the ‘Disability Confident Scheme’ section of the application.

Salary and Benefits Information

This specific role offers a base salary of circa £41,270 - £48,870 per annum (depending on skills and experience) on a full-time basis. We encourage flexible working, part time working and job share arrangements. Part time salary and benefits will be on a pro-rated basis as appropriate.

In addition, we also offer a comprehensive benefits package as detailed below:

• A non-contributory, career average pension giving you a guaranteed retirement benefit of 1/95th of your annual salary for every year worked. There is the option to increase your pension (to 1/50th) or decrease (to 1/120th) in exchange for salary through our flexible benefits programme each year.
• A discretionary performance award based on a current award pool.
• A 7% benefits allowance with the option to take as salary or purchase a wide range of flexible benefits. (Note that for the Benefits year 2023/24, this will increase to 8%)
• 26 days’ annual leave with option to buy up to 12 additional days through flexible benefits.
• Private medical insurance and income protection.

National Security Vetting Process

Employment in this role will be subject to the National Security Vetting clearance process (and typically can take between 6 to 12 weeks post offer) and the passing of additional Bank security checks in accordance with the Bank policy. Further information regarding the vetting and security clearance requirements for the role will be provided to the successful applicant, and information about how the Bank processes personal data for these purposes, is set out in the Bank’s Privacy Notice at Privacy and the Bank of England | Bank of England.

The Application Process

Important: Please ensure that you complete the ‘work history’ section and answer ALL the application questions fully. All candidate applications are anonymised to ensure that our hiring managers will not be able to see your personal information, including your CV, when reviewing your application details at the screening stage. It’s therefore really important that you fill out the work history and application form questions, as your answers will form a critical part of the initial selection process.

The closing date for applications is Friday 26 May 2023.

The assessment process will be comprised of two stages - the first will be a standard interview with the aim of identifying suitable candidates for a data science role within Data & Statistics, while the second shorter interview will be in relation to one or other of the two specific roles available.