HWTS Global
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Overview
Director | Quantitative Recruitment Expert | Connecting Hedge Funds & Prop Trading Firms with High-Calibre Quant Talent | Speed to Market & Quality… We are seeking an experienced
Systematic Credit Quant Trader
with deep expertise in
machine learning and large language models (LLMs)
to design and scale systematic strategies across global credit markets. The ideal candidate will bring a
proven high-Sharpe track record
and strong ability to apply cutting-edge AI techniques to alpha generation. Responsibilities
Research, design, and trade
systematic credit strategies
across cash and derivatives. Apply
advanced machine learning and LLM techniques
to extract signals from unstructured and structured datasets (e.g., news, filings, earnings transcripts, alternative credit data). Build, backtest, and implement models with rigorous risk management and scalability. Partner with developers and data engineers to integrate strategies into production. Continuously improve execution, portfolio construction, and data-driven decision making. Qualifications
Proven live trading track record
with a
high Sharpe ratio
in systematic credit. Minimum
5+ years’ experience
at a top hedge fund, prop desk, or trading firm. Expertise in
machine learning (including deep learning and LLM architectures)
applied to financial markets. Strong programming skills in
Python, C++ or similar , with experience deploying ML pipelines. Deep understanding of
credit markets, fixed income instruments, and credit derivatives . Advanced degree (PhD or Master’s) in Computer Science, Statistics, Machine Learning, Applied Math, or related field.
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Director | Quantitative Recruitment Expert | Connecting Hedge Funds & Prop Trading Firms with High-Calibre Quant Talent | Speed to Market & Quality… We are seeking an experienced
Systematic Credit Quant Trader
with deep expertise in
machine learning and large language models (LLMs)
to design and scale systematic strategies across global credit markets. The ideal candidate will bring a
proven high-Sharpe track record
and strong ability to apply cutting-edge AI techniques to alpha generation. Responsibilities
Research, design, and trade
systematic credit strategies
across cash and derivatives. Apply
advanced machine learning and LLM techniques
to extract signals from unstructured and structured datasets (e.g., news, filings, earnings transcripts, alternative credit data). Build, backtest, and implement models with rigorous risk management and scalability. Partner with developers and data engineers to integrate strategies into production. Continuously improve execution, portfolio construction, and data-driven decision making. Qualifications
Proven live trading track record
with a
high Sharpe ratio
in systematic credit. Minimum
5+ years’ experience
at a top hedge fund, prop desk, or trading firm. Expertise in
machine learning (including deep learning and LLM architectures)
applied to financial markets. Strong programming skills in
Python, C++ or similar , with experience deploying ML pipelines. Deep understanding of
credit markets, fixed income instruments, and credit derivatives . Advanced degree (PhD or Master’s) in Computer Science, Statistics, Machine Learning, Applied Math, or related field.
#J-18808-Ljbffr