CAREERS

MAIN DUTIES/RESPONSIBILITIES OF THE ROLE:

The opportunity is to join a one of Brevan Howard’s largest portfolio management teams in Geneva as a data scientist to work on data-driven research projects including using the latest tools in AI. The hire will work closely with senior portfolio managers and a team of research analysts.

Responsibilities will include

• Design, develop and evolve research workflow & full stack of data science tools

• Develop and maintain engineering best practices including focus on high standards across all stages of research

• Collaborate with other members to translate their needs into scalable, standardized solutions

• Building new tools for conducting statistical analysis over large datasets

• Designing infrastructure to more effectively leverage compute cluster

As such the candidate should have very strong programming skills (Python, Java (or C++), SQL) and must have experience working with large data sets covering different data types (numerical, text, other) and be adaptable to rapidly changing requirements.

WORK EXPERIENCE/BACKGROUNDTECHNICAL/BUSINESS SKILLS & KNOWLEDGE:

Essential

• PHD or masters (with experience) in a quantitative field such as computer science, statistics, mathematics, or a related field. Will also consider candidates with submissions to machine learning competitions or publically available code repos.

• Demonstrable very strong coding skills (Python, Java (or C++), SQL),

• Well-versed in machine learning techniques such as supervised and unsupervised learning, natural language processing, and deep learning

• Solid foundation in statistics and be able to perform various statistical analyses such as hypothesis testing, regression analysis, and time-series analysis

• Broad knowledge & experience of database concepts with proficiency in SQL, databases and big data technologies

• Knowledge of financial data – both numerical and textual

• Experience in processing large and complex datasets

• Emphasis in good engineering practices, design, testing and strategic solutions

• Strong communication skills

• Self-motivated, proactive

• Ability to perform well under pressure

• Enthusiastic, flexible and adaptable

• Ability to work effectively and independently as well as part of a team

• Good interpersonal skills

Desirable

• Other candidates with submissions to machine learning competitions, such as Kaggle, are also encouraged to apply.

• Participation in these competitions demonstrates a strong interest and aptitude in data science and machine learning.

TECHNICAL/BUSINESS SKILLS & KNOWLEDGE:

Essential

• Programming: you should have strong programming skills in languages such as Python. These skills will enable you to manipulate, analyse and visualize large datasets

• Machine learning: you should be well-versed in machine learning techniques such as supervised and unsupervised learning, natural language processing, and deep learning

• Statistical analysis: you should have a solid foundation in statistics and be able to perform various statistical analyses such as hypothesis testing, regression analysis, and time-series analysis

• Data visualization: you should be able to present data in a clear and compelling manner using data visualization tools

• Communication: you should be able to effectively communicate complex data-driven insights to both technical and non-technical stakeholders

• Problem-solving: you should be able to identify and solve complex problems using data-driven approaches

• Continuous learning: you should be committed to continuous learning and staying up-to-date with the latest technologies and trends in data science and finance

Desirable

• Knowledge of latest LLM models and their capabilities / weaknesses

• Knowledge in advanced AI methodologies