Credit Quantitative Researcher

Durlston Partners
City of London
1 week ago
Create job alert

Quantitative Researcher



A leading investment firm is looking to hire a Quantitative Researcher to join a trading team focused on credit markets.



This is a semi systematic role sitting directly on the trading desk, working closely with PMs and researchers to develop models, generate signals, and support investment decisions.



Responsibilities

  • Conduct large scale data analysis across credit markets
  • Develop and improve quantitative models used in the investment process
  • Generate and test signals that feed into trading strategies
  • Work closely with PMs and traders to translate research into production
  • Build tools and analytical frameworks that support the desk



Requirements

  • 2-4 years of experience in a quantitative research
  • Experience analysing single name credit is essential
  • Background from buy-side or sell-side institutions
  • Strong quantitative skills and experience working with financial datasets
  • Candidates must already be based in London



The team is looking to hire quickly, making this an excellent opportunity for someone on the sell-side looking to move closer to the investment process.



If you are interested in learning more, please apply or reach out directly.



Note: If you don't hear back within 3 days, your application was unfortunately not successful.

Related Jobs

View all jobs

Credit Quantitative Researcher

XVA & Collateral Quantitative Researcher

Systematic Credit Quantitative Researcher

Systematic Credit Quantitative Researcher

Systematic Credit Quantitative Researcher

Systematic Credit Quantitative Researcher

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.

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.

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.

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.