Quantitative Financial Analyst - Development Validation

LGBT Great
Edinburgh
2 days ago
Create job alert

At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence.

If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity.

As a Quantitative Financial Analyst - Development Validation, you will ensure the accuracy and quality of financial analytics produced by our asset liability management product. You will serve as the critical bridge between financial theory and implementation, validating that our systems produce correct results aligned with research and industry standards. You will work in a dynamic international environment, collaborating with teams and clients across different countries and time zones.

Primary Responsibilities
  • Review financial analytics requirements and collaborate with Engineering, Product Management and Research to design comprehensive testing strategies
  • Develop independent financial model prototypes and benchmarks using Python, R or MATLAB to validate production implementations
  • Create detailed test cases covering edge cases, stress scenarios, and regulatory requirements
  • Analyze discrepancies between expected and actual results, investigating root causes and working with developers to resolve issues
  • Offer constructive, results-based input to product and engineering teams to support the optimization of financial models
  • Execute and maintain regression test suites to ensure continued accuracy across releases
Skills and competencies
  • 3 to 5 years of experience in a similar role (model validation, quantitative analysis, or financial model development)
  • Master's degree in Financial Engineering, Quantitative Finance, Accounting, Mathematics, Statistics, or closely-related field
  • Good understanding of Financial Risk Models, Fixed Income analysis or Balance Sheet Management
  • Strong analytical skills with a rigorous, quantitative approach to problem-solving
  • Ability to read and implement financial models from technical specifications
  • Proficiency in Excel, knowledge of Python or R or MATLAB
  • Fluency in English, with strong written and verbal communication skills, is a mandatory requirement.
Additional desirable skills
  • Experience with testing frameworks and automation is a plus
  • Programming skills in C++, C# or Java sufficient to understand production code would be a plus
  • Detail-oriented with persistence in identifying and resolving subtle numerical issues
  • Excellent written and verbal communication skills to document findings and explain complex concepts
  • Basic understanding of AI/ML concepts and curiosity about how AI can enhance validation processes
  • Ability to work independently on multiple validation projects while collaborating effectively with cross-functional teams
  • Demonstrated creativity, flexibility, and commitment to continuous learning

Moody’s is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law.
Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody’s Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.


#J-18808-Ljbffr

Related Jobs

View all jobs

Quantitative Validation Analyst — Financial Analytics & AI

Senior Quantitative Finance Analyst, AML Model Risk Validation

Senior Quantitative Finance Analyst, AML Model Risk Validation

Desk Quantitative Analyst

Desk Quantitative Analyst

Quantitative Analyst (Commodities) - Director/Snr Director - London

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.

Neurodiversity in Data Science Careers: Turning Different Thinking into a Superpower

Data science is all about turning messy, real-world information into decisions, products & insights. It sits at the crossroads of maths, coding, business & communication – which means it needs people who see patterns, ask unusual questions & challenge assumptions. That makes data science a natural fit for many neurodivergent people, including those with ADHD, autism & dyslexia. If you’re neurodivergent & thinking about a data science career, you might have heard comments like “you’re too distracted for complex analysis”, “too literal for stakeholder work” or “too disorganised for large projects”. In reality, the same traits that can make traditional environments difficult often line up beautifully with data science work. This guide is written for data science job seekers in the UK. We’ll explore: What neurodiversity means in a data science context How ADHD, autism & dyslexia strengths map to common data science roles Practical workplace adjustments you can request under UK law How to talk about your neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in data science – & how to turn “different thinking” into a real career advantage.

Data Science Recruitment Trends 2025 (UK): What Job Seekers Need To Know About Today’s Hiring Process

Summary: UK data science hiring has shifted from title‑led CV screens to capability‑driven assessments that emphasise rigorous problem framing, high‑quality analytics & modelling, experiment/causality, production awareness (MLOps), governance/ethics, and measurable product or commercial impact. This guide explains what’s changed, what to expect in interviews & how to prepare—especially for product/data scientists, applied ML scientists, decision scientists, econometricians, growth/marketing analysts, and ML‑adjacent data scientists supporting LLM/AI products. Who this is for: Product/decision/data scientists, applied ML scientists, econometrics & causal inference specialists, experimentation leads, analytics engineers crossing into DS, ML generalists with strong statistics, and data scientists collaborating with platform/MLOps teams in the UK.

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.