Quantitative Researcher (Applied Modelling & Financial Analytics)

Chi Square Economics
Newcastle upon Tyne
2 weeks ago
Applications closed

Related Jobs

View all jobs

Quantitative Researcher

Quantitative Researcher- Cross-Asset Relative Value

Quantitative Researcher - Systematic Equities

Quantitative Researcher

Quantitative Researcher - FX

Quantitative Researcher - FX

4 days ago Be among the first 25 applicants

Get AI-powered advice on this job and more exclusive features.

Direct message the job poster from Chi Square Economics

Senior Consultant at Chi Square Economics

Quantitative Researcher (Applied Modelling & Financial Analytics) - competitive salary -

Newcastle Upon Tyne, UK or Madrid, Spain

We’re working with a fast-growing, technically driven consultancy as it expands its quantitative research team in both Newcastle and Madrid. The firm partners with leading financial institutions on a broad range of projects — from pricing and risk analytics to trading tools and model development — offering the chance to apply advanced technical skills to high-impact, real-world problems.

This is an ideal opportunity for someone with a solid foundation in quantitative finance and programming, who is now looking to take on more responsibility and contribute to full-lifecycle development across both research and delivery.

You’ll be working in a team that designs, builds, and implements models and analytical tools used in derivatives pricing, trading, and risk management. The role combines technical depth with hands-on exposure to real financial products and market data.

Responsibilities:

  • Developing and maintaining pricing, risk, and trading models across multiple asset classes
  • Writing clean, production-quality code to support model deployment and tool development
  • Using data and statistical methods to solve practical financial problems
  • Collaborating with stakeholders across quant, dev, and client-facing teams
  • Supporting and enhancing existing models and tools as market needs evolve

The ideal candidate will bring a combination of technical fluency, financial product knowledge, and a strong interest in solving complex challenges. You’ll be comfortable working independently on model development while also contributing as part of a collaborative and fast-paced team.

Key Qualifications

  • Postgraduate degree (MSc or PhD) in a highly quantitative subject (e.g. Mathematics, Physics, Engineering) from a top-tier university
  • Prior experience in financial services or fintech (e.g. investment bank, asset manager, hedge fund, or analytics provider)
  • Working understanding of derivatives pricing, modelling, or risk analytics (e.g. in Rates, Equities, or structured products)
  • Strong coding ability in one or more of: C#, C++, Python, Java
  • Exposure to machine learning or advanced statistical methods is a plus
  • Strong academic performance at A-Level (or equivalent)

Please note: applicants must have the right to work in the UK or Spain. Visa sponsorship is not available for this role.

  • Competitive salary and benefits package
  • Hands-on work in real financial markets with high visibility
  • Fast-paced yet balanced working culture — with a focus on quality, not long hours
  • Opportunities to learn from experienced quants, software engineers, and finance professionals
  • Growth and progression potential in a business with long-term backing and ambitious plans

If you’re looking for a role that builds on your existing experience and challenges you with meaningful work in quantitative finance, this could be a fantastic next step in your career.

Please apply or please reach out to Andrew for a confidential discussion to learn more about this opportunity ().

By applying to this advert you agree to your personal details being held on file in relation to this and other future relevant opportunities.

Seniority level

  • Seniority levelMid-Senior level

Employment type

  • Employment typeFull-time

Job function

  • Job functionAnalyst
  • IndustriesSoftware Development and Financial Services

Referrals increase your chances of interviewing at Chi Square Economics by 2x

Get notified about new Quantitative Researcher jobs in Newcastle Upon Tyne, England, United Kingdom.

Sunderland, England, United Kingdom 3 hours ago

Newcastle Upon Tyne, England, United Kingdom 1 day ago

Newcastle Upon Tyne, England, United Kingdom 1 week ago

Newcastle Upon Tyne, England, United Kingdom 3 weeks ago

Newcastle Upon Tyne, England, United Kingdom 18 hours ago

Newcastle Upon Tyne, England, United Kingdom 4 days ago

Newcastle Upon Tyne, England, United Kingdom 3 days ago

We’re unlocking community knowledge in a new way. Experts add insights directly into each article, started with the help of AI.


#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

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.

Education

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.

Careers Jobs

Data Science Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Thinking about switching into data science in your 30s, 40s or 50s? You’re far from alone. Across the UK, businesses are investing in data science talent to turn data into insight, support better decisions and unlock competitive advantage. But with all the hype about machine learning, Python, AI and data unicorns, it can be hard to separate real opportunities from noise. This article gives you a practical, UK-focused reality check on data science careers for mid-life career switchers — what roles really exist, what skills employers really hire for, how long retraining typically takes, what UK recruiters actually look for and how to craft a compelling career pivot story. Whether you come from finance, marketing, operations, research, project management or another field entirely, there are meaningful pathways into data science — and age itself is not the barrier many people fear.

🍪 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.