Our client, a leading Market Maker in London, seeks to expand its front office Electronic Trading team with the hire of Junior Quant Researcher. With a background in AI, Machine Learning, Natural Language Processing, Digital Signal Processing or Computational Linguistics, you will analyze datasets to develop new, innovative ways of trading and support the existing trading business. This is an exciting opportunity to directly impact a global trading business.

Work with the Snr Quant Strategist in applying scientific methodologies to large financial datasets to develop original insight and a trading edge.
Develop new trading algorithms using in-house quantitative and AI / Machine Learning frameworks
Apply mathematical & programmatic methods for financial markets research across: market microstructure, trading algorithms, participant behavior profiling
Support the existing trading activities; identify trends, make recommendations and produce research notes where appropriate
Stakeholder liaison to improve trade-flows & metrics for performances tracking (trading PnL, risk exposure, etc.)
Enhance quant research frameworks (programmatic & mathematical) to speed-up research, and improve accuracy across datasets


Leading Electronic Market Maker


Minimum of masters educated in a related field (AI, Machine Learning, Natural Language Processing, Digital Signal Processing, Computational Linguistics…)
0-3 years relevant experience (i.e. good fresh PhDs considered)
Strong programming skills in Python, Matlab, R, Java, C++ or C#
Statistics / Probabilistic Processes
Strong background in AI / Machine Learning, NLP or Digital Signal Processing
Analysis of large datasets for insights, recommendations
Great communication skills
Experience of setting up feedback loops to gather information to improve systems
A deep interest in finance and markets/game-theory advantageous

Educational level:

Master Degree

Level of experience (years):

Entry Level (Less than 2 years of Experience)

How to apply:

Please mention NLP People as a source when applying


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