Quantitative Research, Summer Analyst London, UK Programme Overview & Job Description
Quantitative investing is one of the fastest growing segments of the asset management industry today. Bank of America's strong focus on this space is evidenced both from strong growth in a cross asset investable indices business as well as a cross-discipline research effort focused on educating clients (global asset owners and managers) on risk factors, advances in portfolio construction and quantitatively driven systematic strategies across asset classes.
The Quantitative research summer intern within the cross asset quant investment strategy team will help enhance research into and the development of quantitatively driven systematic strategies based on well known risk factors (e.g. Carry, Value, Momentum, Volatility, etc) as well as niche or new areas including higher frequency strategies across asset classes.
Ideally the analyst will benefit from having prior experience of back-testing and/or portfolio construction in any asset class under real world constraints (e.g. liquidity criteria, transaction costs, rebalancing thresholds, etc) and crucially be able to support and stress test empirical results against economic theory. Apart from strategy development and contributing to research published by the firm, the role's scope includes engaging and coordinating internally with global quant research teams, leveraging existing datasets and infrastructure as well as interfacing with the cross asset client solutions teams in Equities and FICC.
Your training and development is our top priority with extensive formal training offered at the start of the programme in addition to on the job support, educational speaker events and mentorship throughout. Qualifications
- Financial market or academic experience of developing and backtesting quantitative investment strategies in Equities or FICC, including risk premia / factor-based investing
- Candidates are required to be pursuing a degree from an accredited college or university with a graduation year of 2024
- Strong academic background in quantitative finance, financial engineering or applied mathematics (e.g. PhD or advanced Masters).
- Advanced proficiency in quantitative analysis and statistics including time series and big / complex datasets
- Exposure/experience in applying machine learning, natural language processing or advanced information theory
- Strong Excel and programming skills, preferably in Python, R, Matlab, VBA, SQL etc
- Fluency in English is essential and a second European language may be required for some roles
- Effective written and presentation skills - a key asset for a quant researcher is to write up and explain often complex concepts in the simplest terms
- Candidates should have a keen eye for detail - accuracy and consistency is crucial in this fast-paced environment
- Candidates must show a long-term interest in the field of quantitative finance and demonstrate achievements towards their pursuit of a career in this field.
- Candidates must demonstrate the ability to work collaboratively and effectively in a team within a fast-paced environment, and show leadership and problem-solving skills.
- Exposure to derivatives a plus
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