Quantitative Trader

We are seeking a Quantitative Trader with a strong background in quantitative finance, mathematics/statistics, financial engineering, or a related background. The ideal candidate will have over two(2) years of experience in quantitative financial model development, operations research, or data science projects. You will play a key role in developing algorithmic trading strategies and enhancing our platform's data analytics.

Job Responsibilities

·         Research, develop, and deploy algorithmic trading strategies and related technical components.

·         Utilize backtesting frameworks and validate against historical data.

·         Work with the portfolio manager to ensure optimal order execution and compliance with the operations and risk management of a public fund.

·         Provide a feedback loop to continuously improve the overall system.

Job Requirements

·         Bachelor's degree or above in Data, finance, or mathematics-related background; a Master's or PhD is advantageous.

·         Software engineering skills and knowledge of data and trading are preferred.

·         2+ years of experience in financial model development, operations research, or data science projects.

·         Knowledge and experience in optimizing computational efficiency for ML models and engineering platforms

·         Experience in HKEx infrastructure and financial products is a must

·         Strong analytical and problem-solving skills.

·         Experience with reinforcement learning and federated learning is a plus.

·         Passionate about AI, Trading in FinTech

·         Proficiency in at least one of the programming languages, such as Python or R.

We offer an attractive package commensurate with your qualifications and experience.

Please apply in confidence with full resume, current and expected salary, quoting reference no. CAFG/QF in the subject line to the CASH Algo Finance Group Limited, 28/F, Manhattan Place, 23 Wang Tai Road, Kowloon Bay, Hong Kong or by clicking "Apply Now".

The information provided will be used for selection purpose only. All information of unsuccessful applicants will be destroyed within six months.