Senior Quantitative Risk Analyst, Risk Analytics, Dublin, Belfast, London, Northampton

AIB (NI)
Belfast
1 month ago
Applications closed

Related Jobs

View all jobs

Senior Data Strategy Consultant, Marketing Solutions

2x Senior Data Engineer (Financial Services)

Data Scientist

Data Science Consultant

Senior Data Engineer

Senior Data Engineer

Senior Quantitative Risk Analyst - Risk Analytics, Level 3

Location: Dublin, Belfast, Northampton, London (Hybrid Working)


In Risk Analytics, we develop and support the deployment of risk models, strategies and decision tools for regulatory capital, internal capital and business decision making. Risk Analytics is part of the Risk Function, an independent, second line of defence that monitors, controls, and supports risk‑taking activities across AIB. The function provides advice, guidance and independent oversight to ensure risks are taken within the appetite set by the Board, supporting AIB’s customer franchise and social responsibility.


Key Accountabilities

  • Analysis & investigation: Undertake and guide junior data scientists in complex data analyses, investigations and modelling of business issues to improve the bank’s services and products.
  • Predictive model development: Lead building of predictive models focused on core business elements such as automated decision‑making, capital requirements and loss expectations.
  • Data insights: Perform and guide junior data scientists in exploratory and ad‑hoc data analysis to generate actionable recommendations for the business.
  • Expert advice: Provide specialist advice on the impact and application of risk management requirements.
  • Risk segmentation analysis: Create segmentations that allow better understanding of risks in the lending portfolio and identify ways to manage those risks.
  • Leadership: Mentor and review the work of junior data scientists.
  • Digital protection: Access and utilise bank data within the policies and frameworks required by AIB.

What you Will Bring

  • Minimum 3 years of experience in a model monitoring, development or validation role (e.g., IRB, IFRS 9, loss forecasting, stress testing, economic capital modelling, propensity modelling).
  • Bachelor’s degree in a quantitative analytical discipline (2.1 or higher) such as mathematics, applied mathematics, physics, statistics, engineering or econometrics.
  • Advanced SAS or SQL programming skills (or equivalent in R, Python, Matlab) with advanced experience in extracting, transforming and cleaning data for modelling.
  • Familiarity with data visualisation tools such as QlikView, Power BI, SAS VA or Tableau.
  • Experience writing technical documents that meet internal and regulatory standards, and engaging with regulatory or audit bodies.
  • Strong relationship‑building and communication skills; curiosity and inventiveness.
  • Good problem‑solving skills with the ability to defend decisions technically and business‑wise.

What We Offer

  • Market‑leading Pension Scheme
  • Healthcare Scheme
  • Variable Pay
  • Employee Assistance Programme
  • Family leave options
  • Two volunteer days per year

Behaviours and Technical Capabilities

  • Ensures Accountability
  • Collaborates
  • Develops & Empowers
  • Data Analysis
  • Risk Modelling & Scenario Analysis
  • Statistical Modelling

Application deadline: 1st April 2026. To be considered for this role you must complete the application process via our careers page.


#J-18808-Ljbffr

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.

Jobs

New Data Science Employers to Watch in 2026: UK and International Companies Leading Analytics and AI Innovation

Data science has emerged as one of the most transformative forces across industries, turning raw information into actionable insights, predictive models, and AI-powered solutions. In 2026, the UK is witnessing a surge in organisations where data science is not just a support function but the core of their products and services. For professionals exploring opportunities on www.DataScience-Jobs.co.uk , identifying these employers early can provide a competitive advantage in a market with high demand for advanced analytics and machine learning expertise. This article highlights new and high-growth data science employers to watch in 2026, focusing on UK startups, scale-ups, and global firms expanding their data science operations locally. All of the companies included have recently raised investment, won high-profile contracts, or significantly scaled their analytics teams.

Careers

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

Jobs

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.