Graduate Quantitative Trader, Digital Assets

We are looking for a graduate trader to join our high-frequency, digital-asset, proprietary trading team.

This individual will be responsible for operating and improving the existing trading algorithms that the team has built. The responsibility of improving existing algorithms requires the ability to analyze data, build trade signals and work as part of a high-performance trading team. In addition to this, the graduate trader will be helping to design and implement new algorithms in the digital asset space.

This role is an excellent opportunity for a university graduate to begin a career in trading. The graduate trader will be working closely with the existing traders in the team, learning from their significant trading experience and growing to become a responsible and profitable contributor to the team.

The graduate trader will experience significant career development in a relatively short time. We are a small team that makes trading decisions as a team, and therefore the graduate trader will obtain unique exposure and responsibilities.

The role requires an individual who is very risk aware and can make rational decisions that are informed by data. The skills that the trader will learn in this role will carry them far in their career. The candidate must exercise a strong interest in digital asset markets as well as excellent competency in the skills needed to build and operate low latency trading algorithms. 

The ideal candidate for the role of graduate trader would demonstrate a keen interest in algorithmic development, a deep understanding of how digital asset market's function and a strong desire to learn about applying technology to trade in digital asset markets. Other important skills include proficiency in working with data, an understanding of security, and some knowledge of data modelling.

Duties and Responsibilities:

• Will be responsible for operating algorithmic trading strategies.
• Must demonstrate trustworthiness and reliability.
• Will be tasked with improving the existing trading algorithms.
• Will help develop logic behind the algorithms.
• Will be helping to design and implement new trading strategies.
• Will be building post-trade analysis and PnL attribution. 

Job Qualifications:

• Candidates will have a strong educational background in a STEM field with a preference to those candidates that have degrees in computer science and statistics. 
• While no previous experience is required, an ideal candidate will be able to demonstrate that they have a keen interest in algorithmic development.
• They will also be able to show that they have a strong desire to learn about applying technology to trade in digital asset markets.
• This candidate must have excellent coding abilities with a focus on algorithms and data; as demonstrated through university, work experience or home projects.
• Concepts to be familiar with: financial markets, trading, probability, expected values, algorithms, multithreaded applications, asynchronous requests, low-latency architecture, API endpoints, basic order book architecture.
• Programming Languages: Java, Python, SQL
• Web: APIs

Knowledge of traditional financial trading architecture is a significant plus. There is an emphasis on soft skills such as communication, teamwork, problem-solving, and adaptability: which are crucial for a successful career in trading.