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Quantitative Researcher

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Onsite

Quantitative Researcher

Fimador

Quantitative Researcher

Skills

PythonJavaData AnalysisMachine Learning

24 days ago

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Important information


Contract type:

Permanent

Location:

London, UK

Work mode:

Onsite

Published on:

4 October 2026

What they need


Fimador is recruiting for a Graduate Quantitative Researcher to join a high-growth firm operating within the banking and financial markets space in the City of London.

This is an opportunity to join a small, highly technical team where quantitative research sits close to real-world trading, pricing and investment decision-making. The role would suit someone who enjoys working in an exciting environment where they can take ownership of research, challenge existing approaches and have a direct impact on the development of quantitative strategies and financial products.

Key Responsibilities:

  • Research and develop quantitative models across financial markets.
  • Analyse large structured and unstructured datasets to identify patterns, signals and market opportunities.
  • Design and implement robust backtesting and research frameworks.
  • Develop statistical, econometric and machine learning models.
  • Work with historical and real-time market data to evaluate model performance.
  • Translate research findings into scalable production solutions.
  • Partner closely with quantitative developers, software engineers and front-office stakeholders.
  • Improve existing models through ongoing validation, optimisation and performance analysis.
  • Build tools and analytics to support trading, pricing and risk decisions.
  • Present research findings and recommendations clearly to technical and commercial stakeholders.

Experience Required - (Not all essential)

  • ( Essential ) Strong academic background in a quantitative discipline such as Mathematics, Statistics, Physics, Computer Science, Engineering, Econometrics or a related subject.
  • Experience within quantitative research, quantitative trading, systematic trading or a closely related area.
  • Strong Python programming skills.
  • Excellent understanding of probability, statistics and statistical modelling.
  • Experience analysing large financial or alternative datasets.
  • Knowledge of time-series analysis, optimisation and backtesting methodologies.
  • Strong understanding of financial markets and market microstructure.
  • Ability to take research from initial hypothesis through testing, validation and implementation.
  • Knowledge of derivatives, equities, fixed income, FX or securities finance.
  • Experience with C++, Java or another high-performance programming language.
  • Familiarity with cloud-based data and research environments.

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