Quantitative Analyst

Quantitative Analyst/Data Scientist – Investments

London – Hybrid

Up to £100,000 + Bonus

About the Role

We are working with an investment company specialising in the credit and lending space.

They are seeking a Quantitative Analyst/Data Scientist to join their growing Credit & Asset-Backed Finance team. This is an opportunity to be part of a specialist group focused on complex, non-corporate credit opportunities across asset-backed finance, lending, and other structured credit situations.

You’ll play a key role in shaping the quantitative capability behind high-value investment decisions, working across modelling, valuation, data infrastructure, and portfolio analytics.

Key Responsibilities

• Building and implementing quantitative models to support pricing, valuation, and risk assessment across asset-backed and structured finance investments.
• Conducting deep-dive analysis into granular loan-level datasets (e.g. consumer, SME, mortgages, receivables) to support investment selection and portfolio monitoring.
• Developing and enhancing analytical tools and systems used to store, process, and monitor investment-related data.
• Working closely with investment, risk, and operations teams to optimise deal structures and maintain robust monitoring frameworks.
• Tracking market movements, regulatory changes, and sector trends to provide insights and recommendations to senior stakeholders.
• Supporting the full investment cycle, from origination and underwriting through to ongoing performance reviews and committee updates.
• Collaborating with colleagues across the wider investment platform to share knowledge and drive best practice.

What We’re Looking For

• Master’s or PhD in Mathematics, Statistics, Physics, Engineering, or another quantitative discipline.
• At least 3 years’ experience in asset-backed finance, structured credit, quantitative analysis, data science, or credit risk.
• Strong experience working with granular loan-level datasets across consumer, SME, real estate, or receivables portfolios.
• Proficiency in Python and a strong command of statistical and financial modelling techniques.
• A solid understanding of asset-backed finance structures and market dynamics.
• Excellent problem-solving skills and strong attention to detail.
• Ability to communicate complex ideas clearly to both technical and non-technical audiences.
• A proactive, high-ownership mindset suited to a fast-paced investment environment.

If this role looks of interest, apply here.