National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

Assistant Vice President, Model Risk Quantitative Analyst

MUFG Americas
London
2 weeks ago
Create job alert

Do you want your voice heard and your actions to count?

Discover your opportunity with Mitsubishi UFJ Financial Group (MUFG), one of the world’s leading financial groups. Across the globe, we’re 120,000 colleagues, striving to make a difference for every client, organization, and community we serve. We stand for our values, building long-term relationships, serving society, and fostering shared and sustainable growth for a better world.

With a vision to be the world’s most trusted financial group, it’s part of our culture to put people first, listen to new and diverse ideas and collaborate toward greater innovation, speed and agility. This means investing in talent, technologies, and tools that empower you to own your career.

Join MUFG, where being inspired is expected and making a meaningful impact is rewarded.

OVERVIEW OF THE DEPARTMENT/SECTION

Enterprise Risk Management (ERM) is responsible for supporting the EMEA Chief Risk Officer to implement an effective risk governance framework across MUFG EMEA, and providing a holistic view of the risks facing MUFG in EMEA, including environmental and social risk management.

The Model Risk Management (MRM) within ERM is responsible for model governance and the validation of models used by MUFG in EMEA. This includes, among others, risk models which are used for risk measurement and decision-making purposes. MRM works closely with Risk Analytics and Front Office quants to ensure that all risk models are validated on a periodic basis as well as at inception and changes. MRM provides regular model risk reporting to model oversight committees and the Board.

MAIN PURPOSE OF THE ROLE

Independent model validation of quantitative methodologies, both initial and periodic, across all asset classes and model types (derivative pricing models, credit and market risk, capital models, AI models, etc. ) and in line with regulatory requirements and industry best practice. The validation regularly requires an independent implementation of the models and the implementation of alternative challenger models.

KEY RESPONSIBILITIES

  • Initial and periodic validation of quant models
  • Designing, modelling and prototyping challenger models
  • Quantitative analysis and review of model frameworks, assumptions, data, and results
  • Testing models numerical implementations and reviewing documentations
  • Checking the adherence to governance requirements
  • Documentation of findings in validation reports, including raising recommendations for model improvements
  • Ensuring models are validated in line with regulatory requirements and industry best practice
  • Tracking remediation of validation recommendations

SKILLS AND EXPERIENCE

Essential:

  • At least a first relevant experience in quantitative modelling (model development or validation) in one or more of these topics:
    • Market risk models
    • Counterparty credit risk models
    • Derivatives pricing models

Optional:

  • Capital models (Economic/Regulatory)
  • Corporate credit risk models (IRB, PD/LGD/EAD)

Competencies:

Essential:

  • Good background in Math and Probability theory - applied to finance.
  • Good knowledge of Data Science and Statistical inference techniques.
  • Good understanding of financial products.
  • Good programming level in Python or R or equivalent.
  • Good knowledge of simulation and numerical methods
  • Awareness of latest technical developments in financial mathematics, pricing, and risk modelling

Beneficial:

  • Experience with AI models
  • Experience with C++ or C# or equivalent

Optional:

  • Up-to-date knowledge of regulatory capital requirements for market and credit risk

Education :

  • A Postgraduate degree in a quantitative discipline (e.g., statistics, mathematics, mathematical finance, econometrics)

PERSONAL REQUIREMENTS

  • Strong problem solving skills
  • Strong numerical skills
  • A structured and logical approach to work
  • Excellent attention to detail
  • Excellent written and oral communication skills
  • Ability to clearly explain technical matters
  • A pro-active, motivated approach

PERFORMANCE AND DUTIES

We are open to considering flexible working requests in line with organisational requirements.

MUFG is committed to embracing diversity and building an inclusive culture where all employees are valued, respected and their opinions count. We support the principles of equality, diversity and inclusion in recruitment and employment, and oppose all forms of discrimination on the grounds of age, sex, gender, sexual orientation, disability, pregnancy and maternity, race, gender reassignment, religion or belief and marriage or civil partnership.

We make our recruitment decisions in a non-discriminatory manner in accordance with our commitment to identifying the right skills for the right role and our obligations under the law.


#J-18808-Ljbffr

Related Jobs

View all jobs

Assistant Vice President, Model Risk Quantitative Analyst

Quantitative Analyst, Model Validation, AVP

Assistant Vice President, EIA Data Analytics

Quantitative Research - Credit - Vice President

Quantitative Research - Credit - Vice President

Quantitative Research - Credit - Vice President

National AI Awards 2025

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.

Data Science Jobs UK 2025: 50 Companies Hiring Now

Bookmark this guide—refreshed every quarter—so you always know who’s really expanding their data‑science teams. Budgets for predictive analytics, GenAI pilots & real‑time decision engines keep climbing in 2025. The UK’s National AI Strategy, tax relief for R&D & a sharp rise in cloud adoption mean employers need applied scientists, ML engineers, experiment designers, causal‑inference specialists & analytics leaders—right now. Below you’ll find 50 organisations that have advertised UK‑based data‑science vacancies or announced head‑count growth during the past eight weeks. They’re grouped into five quick‑scan categories so you can jump straight to the kind of employer—& culture—that suits you. For every company you’ll see: Main UK hub Example live or recent vacancy Why it’s worth a look (tech stack, mission, culture) Search any employer on DataScience‑Jobs.co.uk to view current ads, or set up a free alert so fresh openings land straight in your inbox.

Return-to-Work Pathways: Relaunch Your Data Science Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like stepping into a whole new world—especially in a dynamic field like data science. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s data science sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve gained and provide mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for data science talent in the UK Leverage your organisational, communication and analytical skills in data science roles Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to data science Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to data science Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as a data analyst, machine learning engineer, data visualisation specialist or data science manager, this article will map out the steps and resources you need to reignite your data science career.

LinkedIn Profile Checklist for Data Science Jobs: 10 Tweaks to Elevate Recruiter Engagement

Data science recruiters often sift through dozens of profiles to find candidates skilled in Python, machine learning, statistical modelling and data visualisation—sometimes before roles even open. A generic LinkedIn profile won’t suffice in this data-driven era. This step-by-step LinkedIn for data science jobs checklist outlines ten targeted tweaks to elevate recruiter engagement. Whether you’re an aspiring junior data scientist, a specialist in MLOps, or a seasoned analytics leader, these optimisations will sharpen your profile’s search relevance and demonstrate your analytical impact.