Quant Trader

Quant Trader

London Full-Time No home office possible
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Qualifications

A Ph.D. in Computer Science, Econometrics, Electronic Engineering, Mathematics, Physics or Statistics. You will have a track record of published research work in respected journals. Applications from candidates who have completed a post-doctoral research position are particularly welcome.

Relevant Experience

Successful candidates will have substantial academic or trading experience in at least one of the following areas:

  • Applied Mathematics such as Cryptography, Fluid Mechanics, and Optimisation.
  • Linear and non-linear time series and spectral analysis (ARIMA, TAR, VAR, SSA etc.)
  • Machine learning techniques such as DNN\’s, LSTM, LASSO, Random Forest, and XGBoost.
  • Multivariate methods such as PCA and ICA, Factor Analysis, and Cluster Analysis.

Essential Skills:

  • Experienced in C++ on very large data sets.
  • Self-motivated with high curiosity.
  • Ability to work independently and with a team.

Benefits

  • Work alongside similar people in an innovative research-driven environment.
  • Ability to use new research techniques on ever-growing data sets.
  • Highly competitive annual bonus payments to successful candidates who demonstrate positive innovation in models and processes.

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Contact Detail:

eFinancialCareers Recruiting Team

Quant Trader
eFinancialCareers
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