Quantitative Analyst

1 day ago

City of London, United Kingdom Harnham Full time

Quantitative Analyst/Data Scientist – InvestmentsLondon – HybridUp to £100,000 + BonusAbout the RoleWe 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 ResponsibilitiesBuilding 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 ForMaster’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.

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