Private and Investment Bankers since 1964. CIGP Group, built by entrepreneurs, is an independent global advisory firm that offers a one-stop-shop platform made for entrepreneurs, business owners and families who are looking for trusted partners capable of delivering institutional grade solutions to their needs.

Our activities cover wealth and asset management, as well as investment banking services to a sophisticated and international clientele, looking to develop and invest in Europe and Asia. Over the last 3 years, we developed our proprietary AI-based quantitative investment framework leveraging the power of big data to identify investment opportunities.

We are looking for a Research Engineer in our Hong Kong office, starting as soon as possible for 6 months as an intern (with the possibility to be converted into a full-time role), to assist in the continuous improvement of our quantitative investment framework by developing a Reinforcement Learning model. The candidate shall have prior experience in Reinforcement Learning, a curious, open, and flexible mind, possess excellent mathematical and programming skills and demonstrate a strong level of responsibility. They must be keen to analyze financial datasets and instruments with statistical and machine learning tools in combination with human insights to help answer significant investment problems. Our entrepreneurial culture fosters candidates which seek to pursue opportunities on their own initiative.

Requirements

The Research Engineer will work closely with the Quantitative Research team which continuously pursues new performance-enhancing opportunities to enrich our investment framework. The candidate will develop a Reinforcement Learning model providing recommendations based on multiple inputs with the goal of implementing it in our strategy after successful backtesting. The role is an excellent opportunity for candidates looking to evolve within an entrepreneurial environment where they can make an impact from day one. 

Objectives: 

• Design and develop, in coordination with the team, a Reinforcement Learning model taking investment decisions based on market signals and operational considerations
• Test and analyse continuously the model’s behaviour under various market conditions to make relevant adjustments
• Report and present experimental results to the team in a clear and concise manner
• Document the model and research approach in a white paper
• Implement the solution by leveraging modern hardware and distributed computing systems, in a cost-conscious/efficient way

Required Skills and Talents:

• Currently completing or completed a Master’s degree in Computer Science, Mathematics, Statistics, or another highly quantitative field
• Excellent knowledge of mathematics, probability, and statistics (machine learning, time-series analysis)
• Experience in developing Reinforcement Learning models demonstrated via prior positions, contribution to open source or coding competitions
• Excellent Python skills and proficiency with relevant machine learning libraries: TensorFlow/PyTorch/Keras
• Experience with NoSQL databases (e.g., MongoDB) and distributed computing (e.g., Dask)
• Efficient with a strong attention to detail, quality, and scalability
• Strong written and verbal communication skills with ability to present information clearly and concisely
• Good team player, highly flexible and always willing to deliver high quality work, exceed targets/goals set while meeting deadlines.
• Open to criticism, altruist, and strong ethical standards (respectful, trustworthy, transparent & honest) are essential traits.
• Full working proficiency in English (reading, writing, and speaking). Any additional language is a plus.