Quant Researcher

SUMMARY:

Golden Horse Fund Management is one of the fastest growing fund management companies in Asia. We employ proprietary statistical and machine learning techniques to analyse large volumes of data to optimally improve and fine-tune our strategies. Our investment team is seeking a highly motivated individual keen in the fund management industry to develop AI investment solutions. As part of investment team, you will have the chance to work with a team of dedicated experts in market data analysis and quantitative trading. An ideal candidate will have an excellent record of academic achievements, solid technical skills, and experience in AI model development.

KEY RESPONSIBILITIES:

1. Technical Strategy: Develop and implement technical strategies that align with hedge fund business objectives, leveraging advanced quantitative methods and machine learning techniques.
2. Team Management: Collaborate closely with the CEO and a team of developers, engineers, and technical staff to drive innovative research initiatives and system enhancements.
3. Technical Guidance: Provide expert technical guidance and oversight for projects, particularly in areas of quantitative analysis and algorithm development.
4. Architecture and Design: Design and implement scalable, secure, and high-performance system architectures, incorporating advanced data analysis and modeling techniques.
5. Vendor Management: Manage relationships with technology vendors and service providers, ensuring alignment with the firm's technical and research objectives.
6. Research and Trade Idea Generation: Conduct in-depth research to generate trade ideas, utilizing quantitative models and macroeconomic analysis to inform investment decisions.
7. Portfolio Risk and Profitability Analysis: Analyze portfolio risk and profitability, applying quantitative methods to assess and optimize portfolio performance.
8. Market Reporting and Forecasting: Prepare daily, monthly, and quarterly market reports and forecasts for senior management and external stakeholders, integrating quantitative insights.
9. Portfolio Performance Reporting: Deliver comprehensive portfolio performance analyses to senior management and external stakeholders, emphasizing quantitative metrics.
10. NAV Report Review and Trade File Submission: Assist in reviewing NAV reports from fund administrators and submitting monthly trade files, ensuring accuracy and compliance.
11. Strategy Research, Development, and Back-testing: Lead research, development, and back-testing of quantitative and fundamental strategies, utilizing advanced statistical and machine learning techniques.
12. AI Solution Development: Collaborate with the team to develop and enhance AI solutions aimed at predicting market trends and optimizing portfolio performance.
13. Marketing and Investor Relations Support: Support marketing and investor relations functions by contributing to the development of materials that highlight quantitative research and performance metrics.
14. Government Grants and Loans Sourcing: Identify and source government loans and grants available in the industry, supporting research and development initiatives.
15. Regulatory and Tax Updates: Provide timely updates on regulatory changes and tax authority communications, ensuring the firm's compliance and strategic alignment.
16. Ad Hoc Administrative Duties: Perform other administrative duties as required, supporting the seamless operation of the technical and research teams.

QUALIFICATIONS:

1. Educational Background: Master in a quantitative discipline (e.g. Mathematics/Statistics, Economics, Quantitative Finance, Financial Engineering, etc) with proven academic achievement and clear ability to handle data and perform quantitative analysis
2. Professional Experience: Experience in quantitative research roles, demonstrating a solid track record in financial research and analysis.
3. Programming Proficiency: Advanced proficiency in Python and C++, Java, MySQL, Matlab, R, Latex, with practical experience in developing quantitative models and conducting data analysis.
4. Machine Learning Expertise: Extensive experience with machine learning algorithms and deep learning frameworks such as TensorFlow and PyTorch, applied to financial data analysis and strategy development.
5. NLP Knowledge: In-depth understanding of the latest NLP technologies, with hands-on experience in developing NLP models for financial applications.
6. Multitasking and Attention to Detail: Proven ability to manage multiple tasks simultaneously with a high degree of accuracy and attention to detail, ensuring quality and precision in all deliverables.
7. Passion for Investment: A strong passion for investment, demonstrated through academic pursuits and practical research, aligning with the firm's commitment to innovative investment strategies.

COMMITMENT:

Monday to Friday Office Hours