Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Quantitative Business Analyst – Risk Technology (PFE / Credit Risk) (m/f/d)

emagine
City of London
2 days ago
Create job alert
Overview

Quantitative Business Analyst – Risk Technology (PFE / Credit Risk) (m/f/d)


London x5 Days on-site


£600-£650


emagine is a high-end professional services consultancy and solutions firm specialising in providing business and technology services to the financial services sector, we power progress, solve challenges and deliver real results through tailored high-end consulting services and solutions.


We have created a culture of openness and integrity by building genuine and strong relationships and partnerships, enabling us to be uncompromising in our dedication in delivering the optimal service for our clients. Our commitment is not just towards our clients but we aim to foster a positive and equitable working environment with our consultants and colleagues which stems from our core values: Confident, Dedicated, Responsible, Genuine.


We are currently looking for Quantative Business Analyst to support the delivery and adoption of a Potential Future Exposure (PFE) initiative. This role is critical for meeting regulatory requirements (e.g., PRA/ECB) and ensuring consistent and robust credit risk methodologies across the organisation. This role will be responsible for supporting the implementation of PFE and intraday/end-of-day credit risk monitoring, with a strong emphasis on quantitative analysis and validation. The role will require engagement with risk quants, validation of pricing and simulation models, mapping of complex products, and involvement in rigorous testing of risk models and systems.


Responsibilities

  • Act as a Quantitative BA within the PFE programme, bridging the gap between risk quants, technology, and business stakeholders.
  • Perform detailed quantitative and technical analysis of PFE methodologies and infrastructure design.
  • Document and validate user requirements with a focus on credit exposure modelling and risk factor behaviour.
  • Support validation of pricing models, simulation engines, and PFE calculations using vendor or in-house tools.
  • Map complex products (Interest Rates, FX, Loans, and derivatives) into PFE model frameworks, ensuring consistency across modelled and non-modelled approaches.
  • Collaborate with risk quants to understand methodology design and communicate requirements to development teams.
  • Define and execute structured testing methodologies, including quantitative validation, regression testing, and end-to-end model testing.
  • Partner with production teams to ensure smooth deployment of new quantitative risk processes and controls.
  • Provide subject matter expertise in quantitative risk technology to resolve production issues and influence future platform enhancements.
  • Build strong working relationships across risk analytics, model validation, market and credit risk management, technology, and front office teams.

Key Skills and Experience

  • Hands-on experience with counterparty credit risk and advanced PFE methodologies.
  • Familiarity with stochastic simulation, exposure profiles, and risk factor modelling.
  • Practical experience working with vendor or proprietary pricing and risk engines (e.g., FraimWRX, Murex, or similar).
  • Knowledge of investment banking products and their quantitative characteristics (Interest Rate derivatives, FX, Loans).
  • Strong business analysis skills, including requirements gathering, functional specifications, and test planning.
  • Demonstrated ability to validate and interpret quantitative model outputs, liaising effectively with risk quants.
  • Minimum 5 years’ experience in risk technology, credit risk, or quantitative business analysis roles.
  • Excellent communication skills, with the ability to explain quantitative concepts to non-quant stakeholders. Previous work experience in investment banking or the securities industry, ideally in a quantitative BA or risk technology role.
  • Proactive, self-starting, and detail-oriented with strong ownership of deliverables.
  • Strong analytical, problem-solving, and decision-making skills.
  • Ability to manage workload across multiple priorities, balancing urgent tasks with long-term projects.
  • Strong interpersonal and influencing skills, with the ability to partner across technical and business teams.
  • High attention to detail and accuracy, particularly in quantitative analysis and testing.

Our people

The ideal consultants will share our values and be aligned with our ways of working and as your career progresses, you can expect to work across all areas of the project lifecycle, from strategy to implementation. This will provide you with a broad base of experience from which to build an outstanding career.



  • Providing our people with a supportive culture, rooted in our values and driven by our purpose.
  • Promoting a culture of inclusion, collaboration, well-being, and learning and development.
  • Providing increased agility and flexibility within our hybrid working model
  • Investing in employees’ growth through ongoing training and development
  • Autonomy to take ownership of projects, making decisions and demonstrating individual expertise
  • Providing a transparent performance and career management experience.

EEO statement

emagine is an equal opportunity employer, and employment practices are based strictly on merit. It is the policy of the Company to give equal opportunity in employment regardless of sex, sexual orientation, marital status, race, age, disability, gender reassignment, pregnancy and maternity, religion or ethnic origin.


Seniorities

  • Mid-Senior level

Employment type

  • Full-time

Job function

  • Research, Analyst, and Information Technology

Industries

  • IT Services and IT Consulting


#J-18808-Ljbffr

Related Jobs

View all jobs

Senior Quantitative Finance Analyst - Quantitative Developer

2026 Summer Analyst – Quantitative Technology Services

2026 Summer Analyst - Quantitative Technology Services

2026 EMEA London Finance and Risk Quantitative Strats Summer Analyst

2026 | EMEA | London | Finance and Risk Quantitative Strats | Summer Analyst

Senior Quantitative Analyst

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Why Data Science Careers in the UK Are Becoming More Multidisciplinary

Data science once meant advanced statistics, machine learning models and coding in Python or R. In the UK today, it has become one of the most in-demand professions across sectors — from healthcare to finance, retail to government. But as the field matures, employers now expect more than technical modelling skills. Modern data science is multidisciplinary. It requires not just coding and algorithms, but also legal knowledge, ethical reasoning, psychological insight, linguistic clarity and human-centred design. Data scientists are expected to interpret, communicate and apply data responsibly, with awareness of law, human behaviour and accessibility. In this article, we’ll explore why data science careers in the UK are becoming more multidisciplinary, how these five disciplines intersect with data science, and what job-seekers & employers need to know to succeed in this transformed field.

Data Science Team Structures Explained: Who Does What in a Modern Data Science Department

Data science is one of the most in-demand, dynamic, and multidisciplinary areas in the UK tech and business landscape. Organisations from finance, retail, health, government, and beyond are using data to drive decisions, automate processes, personalise services, predict trends, detect fraud, and more. To do that well, companies don’t just need good data scientists; they need teams with clearly defined roles, responsibilities, workflows, collaboration, and governance. If you're aiming for a role in data science or recruiting for one, understanding the structure of a data science department—and who does what—can make all the difference. This article breaks down the key roles, how they interact across the lifecycle of a data science project, what skills and qualifications are typical in the UK, expected salary ranges, challenges, trends, and how to build or grow an effective team.

Why the UK Could Be the World’s Next Data Science Jobs Hub

Data science is arguably the most transformative technological field of the 21st century. From powering artificial intelligence algorithms to enabling complex business decisions, data science is essential across sectors. As organisations leverage data more rapidly—from retailers predicting customer behaviour to health providers diagnosing conditions—demand for proficiency in data science continues to surge. The United Kingdom is particularly well-positioned to become a global data science jobs hub. With world-class universities, a strong tech sector, growing AI infrastructure, and supportive policy environments, the UK is poised for growth. This article delves into why the UK could emerge as a leading destination for data science careers, explores the job market’s current state, outlines future opportunities, highlights challenges, and charts what must happen to realise this vision.