MFS is looking to improve its trade execution quality across asset classes and globally by developing and expanding its analytics platform, driving automation, and enhancing decision-making for the Trading team.
Requirements
- Experience with Python, KDB/Q or other programming languages with a focus on interfacing with high volume data.
- Experience working with large data sets, structured and unstructured
- Experience with data visualization and concepts around display of data
- Equity and fixed income quantitative background, market structure knowledge, plus experience with trading processes and/or transaction cost analysis (TCA).
- Thorough understanding of quantitative financial and statistical concepts.
Responsibilities
- Conduct execution research and analysis globally, across asset classes.
- Proactively and independently develop quantitative analyses and tools to support and enhance the execution of trading ideas.
- Provide regular and ad hoc reporting/data visualization as output of analysis.
- Find and action opportunities for automation in analysis production and in the trading process.
- Improve the availability and quality of internal and external data and analysis.
- Maintain and manage third party post-trade execution analytic and vendor relationships.
- Independently discover and evaluate tools and vendors that can enhance the trading process.
Other
- Master's degree or equivalent in a relevant field such as finance with some experience in software engineering, statistics, or data science.
- Minimum of three to five years of trading, transaction cost analysis or related experience.
- Ability to work independently and proactively generate project ideas.
- Strong interpersonal and communication skills.
- Some international travel.
