As a Trading Analytics and Strategy Analyst within the Global Trading Analytics and Strategy team, you will be focused on the quantitative analysis of trading performance and strategy development. This involves detailed transaction cost analysis (TCA), design of systematic trading strategies, and supporting the ongoing trading process. You will have the opportunity to work with a global team and use a global trading analytics platform. Your key responsibilities will include conducting trading research projects, co-developing and assisting in the implementation of systematic trading systems/strategies, and managing the health and development of the analytics platform for the US region. This role provides a great opportunity to enhance your skills in data analytics, SQL/database queries, and financial data analysis.
Job Responsibilities:
- Conduct trading research projects to enhance the overall investment process
- ·Co-develop and assist in the implementation of systematic trading systems/strategies with traders and technology teams
- ·Enhance the tools and processes used to monitor the performance of brokers, traders and strategies
- ·Manage the health and development of the analytics platform for the US region (e.g. OMS/EMS data feeds and market data services)
- Perform independent research by analyzing large datasets, especially tick data and drawing actionable insights
Required qualifications, capabilities and skills
- Professional experience in a programming language for data analytics (Python/R/Matlab)
- Proficiency in constructing and analyzing SQL/database queries
- Experience in a trading, strategist or analytics role
- Ability to present ideas in a clear and concise manner to traders and senior investors
- Good understanding of US equity market microstructure
- Good understanding of technology development methods and strong working relationships with technology teams in delivering large scale projects
- Hands on experience in statistical modelling, time series analysis and exploratory data analysis on financial data
Preferred qualifications, capabilities and skills:
- · CFA / CQF
- · Knowledge and experience in machine learning
- · Knowledge and experience in various OMS /EMS data models
- · Past experience working in a global teams