Senior Risk Analyst (Data Scientist) in Operational Risk and Capital Intelligence
Compensation
Not disclosed
Location
Leeds, United Kingdom
Work setup
Not specified
Seniority
Senior
Employment
Part time
Experience
Not specified
Category
Data science
Posted
Skills
analytics
data-quality
data-science
data-visualization
machine-learning
powerbi
python
sql
statistics
Must have
Relevant professional experience applying data science, statistical analysis or advanced analytical techniques to business, risk, regulatory or policy-related problems.
Working knowledge of the data science lifecycle, including data acquisition, preparation, analysis, visualisation and interpretation.
Experience using analytical and visualisation tools such as Python, R, SQL, Power BI or equivalent data science technologies.
Experience working with structured and unstructured datasets to identify trends, patterns and actionable insights.
Ability to communicate technical findings clearly and effectively to non-technical audiences.
Strong analytical and problem-solving skills, including the ability to work with uncertainty, assumptions and incomplete information.
Experience collaborating with subject matter experts to support evidence-based decision-making.
Nice to have
Experience applying machine learning, artificial intelligence or advanced statistical techniques to practical business, risk or regulatory challenges.
Knowledge of operational risk, operational resilience, technology risk, cyber risk or operational risk capital concepts.
Relevant professional qualifications or academic qualifications in data science, statistics, mathematics, computer science, operational research or a related discipline.
Interest in emerging technologies, data science innovation and their application to supervisory and financial stability challenges.
As a directorate of the PRA, the Supervisory Risk Specialists (SRS) provides deep technical expertise and applies judgement in specific risk disciplines in order to identify, analyse and mitigate material risks to the safety and soundness of PRA regulated firms as well as financial stability objectives. SRS also supports the wider Bank through providing risk specialist expertise to a range of functions including policy development and implementation, the Bank's concurrent stress tests, Concurrent Operational Resilience Stress Testing, central counterparty and payments oversight.
SRS comprises five divisions:
Operational Risk & Resilience (ORRD)
Sector Resilience Division (SRD)
Credit, Risk, Analytics, Liquidity and Capital (CRACL)
Investment Banking and Sector Risks (IBSR)
Model Development and Review (MDRD)
Operational Risk & Resilience Division
The Operational Risk and Resilience Division (ORRD), part of the SRS Directorate, plays a pivotal role in shaping the PRA’s supervisory approach to operational risk and resilience. This is a unique opportunity to contribute to the evolution of ORR policy and practice, influencing both regulatory and financial stability agendas. The work spans system-wide issues and engages with central banks, regulators, and government agencies at both domestic and international levels, giving you an opportunity to shape strategic developments in operational risk and resilience.
Operational Risk and Capital Intelligence Team
The Operational Risk and Capital Intelligence team is responsible for developing the tools and insights needed to drive a system-wide view of operational risk management, capital and related emerging trends. These allow ORRD to prioritise what matters most and strengthen the evidence base for capital judgements and how they integrate with the division’s broader risk & resilience toolkit using a combination of quantitative and qualitative assessment methods.
Job Description
An opportunity has arisen for a Senior Risk Analyst (Data Scientist) in the Operational Risk and Capital Intelligence team.
Responsibilities
Applies data science, statistical and analytical techniques to operational risk and resilience data to support supervisory assessments and decision making.
Identifies, collates and analyses internal and external datasets to generate insights relevant to all aspects of operational risk and resilience.
Develops and maintains analytical tools, dashboards, visualisations and models that support consistent and evidence-based supervisory assessments.
Supports the formulation of analytical questions and hypotheses by working closely with operational risk, resilience, technology risk and capital specialists.
Produces high-quality analytical outputs, presenting findings clearly and accurately to technical and non-technical audiences.
Applies appropriate analytical methodologies and exercises sound judgement when working with imperfect, incomplete or complex datasets.
Contributes to cross-firm analysis, thematic reviews and the development of the division's risk and resilience toolkit and seeks to improve how data is presented and curated.
Promotes good analytical practice, data quality and effective use of analytical tools and techniques within the team.
Maintains awareness of developments in data science, emerging technologies and analytical techniques, identifying opportunities for application to supervisory challenges.
Leads discrete analytical workstreams, supports prioritisation of analytical effort and contributes to shaping the division’s data strategy.
Requirements
Minimum Criteria
Relevant professional experience applying data science, statistical analysis or advanced analytical techniques to business, risk, regulatory or policy-related problems.
Working knowledge of the data science lifecycle, including data acquisition, preparation, analysis, visualisation and interpretation.
Experience using analytical and visualisation tools such as Python, R, SQL, Power BI or equivalent data science technologies.
Experience working with structured and unstructured datasets to identify trends, patterns and actionable insights.
Ability to communicate technical findings clearly and effectively to non-technical audiences.
Strong analytical and problem-solving skills, including the ability to work with uncertainty, assumptions and incomplete information.
Experience collaborating with subject matter experts to support evidence-based decision-making.
Essential Criteria
Experience applying data science, quantitative analysis or statistical techniques to solve complex analytical and business problems.
Ability to identify, extract and analyse information from multiple data sources to generate insight relevant to risk management, supervision or organisational decision-making.
Experience developing analytical tools, dashboards, visualisations or models that help answer business questions and improve consistency of analysis.
Ability to translate business questions into analytical hypotheses and use appropriate techniques to investigate and answer them.
Strong communication and stakeholder engagement skills, with the ability to explain complex analytical concepts, methodologies, assumptions, and limitations in a clear and accessible way to both technical and non-technical audiences, while demonstrating their relevance to business decisions and outcomes.
Experience working effectively with multidisciplinary teams, consolidating inputs and turning them into analytical insights that elevate key risks and help answer key business questions.
Understanding of data quality considerations and the importance of robust analytical practices, controls and governance.
Ability to work independently, prioritise competing demands and deliver high-quality analytical outputs to agreed timescales.
Demonstrated curiosity and willingness to explore new analytical techniques, data sources and approaches to improve insight and decision-making.
Desirable Criteria
Experience applying machine learning, artificial intelligence or advanced statistical techniques to practical business, risk or regulatory challenges.
Knowledge of operational risk, operational resilience, technology risk, cyber risk or operational risk capital concepts.
Relevant professional qualifications or academic qualifications in data science, statistics, mathematics, computer science, operational research or a related discipline.
Interest in emerging technologies, data science innovation and their application to supervisory and financial stability challenges.
What will I get from the role?
Develop and apply data science techniques to real-world supervisory challenges that matter for the safety and soundness of firms and the resilience of the UK financial system.
Gain exposure to a wide range of operational risk, technology risk and resilience topics while working alongside leading subject matter experts from across the PRA and the wider Bank.
Build expertise in advanced analytics, data visualisation and data-driven decision-making within a unique regulatory environment.
Contribute to the development of innovative analytical tools and approaches that strengthen the PRA's evidence base and supervisory toolkit.
Undertake intellectually stimulating work at the intersection of data science, risk management and financial stability.
Develop a strong professional network across operational risk, resilience, cyber risk, capital and analytical communities within the Bank.
Additional Information – externalOur 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 50% 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. 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
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.
We offer a salary circa £51,360 - £57,700. In addition, we also offer a comprehensive benefits package as detailed below:
Currently a non-contributory, career average pension giving you a guaranteed retirement benefit of 1/80th of your annual salary for every year worked. There is the option to increase your pension (to 1/65th) or decrease (to 1/105th) in exchange for salary through our flexible benefits programme each year. The Bank has the discretion to vary standard accrual rates and dial up and dial down rates at any time and to withdraw dial up and dial down options at any time.
A discretionary performance award based on a current award pool.
An 8% benefits allowance with the option to take as salary or purchase a wide range of flexible benefits.
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.
The Bank of England welcomes applications from all candidates, but as a UK Visas and Immigration (UKVI) approved sponsor, we have a responsibility to comply with the Immigration Rules and guidance. As such, our ability to employ individuals who require sponsorship for immigration purposes is limited. The Bank cannot guarantee that you and / or the role you are applying for will be eligible for sponsorship and that any application made to UKVI will be successful. Eligibility will therefore be considered on a case by case basis.
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.
This role closes on 2nd Nov.
The assessment process will comprise of two interview stages.
Please apply online, ensuring that you complete your work history and answer ALL the application questions fully and in detail as your application will not be considered if all mandatory questions are not fully completed.