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    Systematic Machine Learning Quant Researcher - Singapore - TECHNOLOGY SERVICES GROUP PTE. LTD.

    TECHNOLOGY SERVICES GROUP PTE. LTD.
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    Description
    Roles & Responsibilities

    Leading AI quant fund are looking to hire a machine learning quant researcher onto their systematic team.

    Role:

    • Conduct quantitative research with PM and other AI quants to develop and back-test different machine learning and statistical models, as well as productionize such models.
    • Combine sound financial insights and machine learning techniques to explore, analyze, and harness a large variety of datasets.
    • Use a rigorous scientific method to develop sophisticated trading models and shape our insights into how the markets will behave.
    • Apply machine learning to a vast array of datasets
    • Focuses on Time-Series Transformers Based such as TFT
    • Focuses on Pytorch Forecasting, GlutonTS, NeuralForecast Stacks
    • Understanding the difference between autoregressive versus latent properties

    Requirements:

    • Masters/PhD degree in Mathematics, Physics, Financial Engineering, Computer Science, Statistics with specialization in Machine Learning
    • Experience working with large datasets and machine learning techniques
    • Experience in one or more of deep learning, reinforcement learning, non-convex optimization, Bayesian non-parametrics, NLP or approximate inference.
    • Publications at top conferences such as NeurIPS, ICML, ICLR etc. is highly desirable.
    • Experience in a high-performance language (ideally C++, or similar languages)
    • Outstanding performance in any quantitative field or contest (Kaggle, hackathons, Olympiads, academic contests etc.).
    • Experience implementing machine learning algorithms in industry.
    • Open to ML quants who are already working within finance or ML quants within tech who are interested to move to finance.
    • Trading Background is not a pre-requisite for the above role.
    Tell employers what skills you have

    TensorFlow
    Machine Learning
    Forecasting
    Sampling
    Quantitative Research
    Financial Engineering
    Physics
    Mathematics
    Software Engineering
    Data Engineering
    PyTorch
    Speech Recognition
    Anomaly Detection
    Statistics
    Publications
    C++

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