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    Quant Trader - London, United Kingdom - eFinancialCareers

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    Full time
    Description

    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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