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Python Dev - Financial services

Job in Greater London, London, Greater London, EC1A, England, UK
Listing for: Talan Group
Full Time position
Listed on 2026-01-13
Job specializations:
  • Software Development
    Data Scientist, Data Engineer
Job Description & How to Apply Below
Location: Greater London

Talan is an international consulting group in innovation and transformation through technology. For 20 years, Talan has been advising companies and administrations. The group supports them and implements their transformation and innovation projects internationally.

Present on five continents, the group achieved a turnover of 800 million euros in 2024 for more than 8,000 consultants and aims to exceed the one billion € turnover mark by 2025.

To work at one of our clients, we are seeking an Python Developer / Quant Dev

Job Description

The Global Markets Quantitative Research division of our client is in charge of the modelling, pricing & risk management developments for the entire offering of products within the Global Markets activity.

The team operates globally with representatives in London, Paris, Asia, and New York and plays a critical role in providing innovative solutions.

Inside GMQR, Histo team works on a wide range of applications, from booking systems, real time price computation to market data storage and high performance transfer, and a wide range of tasks from algorithm design and refinement, user experience to hardware selection and network performance analysis.

One of our missions is also to provide quantsupport services for the Delta One trading desks, that's why we are currently looking for Quant Dev consultant (one junior 0 to 3 years of experience).

The ideal candidate will possess strong technical skills, problem-solving abilities, and effective teamwork.

Key responsibilities:

  • Strengthen and enhance reliability of solutions dedicated to ETF market making activity
  • Build scalable systems for large-scale data analysis and experimentation
  • Evaluate and implement third-party tools and data sources
  • Ensure that Risks and P&L are properly assessed and computed
  • Contribute to research discussions and improve methodologies
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