Senior research Analyst/ Quantitative Researcher
• Lead and initiate new research projects concerned with alpha and factor modelling, variable construction, and portfolio construction research projects. Provide a strong voice in discussions about existing and new research projects.
• Work closely with client portfolio management teams as required to meet client requests, and address ongoing product support through quantitative research and analysis.
• Support and initiative ideas within the strategies teams to monitor model performance, analyze model effectiveness, develop analytics, and consider potential enhancements as it relates to client portfolios and assigned strategies.
• Be closely connected with industry research and trends and share relevant material with the research and portfolio management teams to ensure that new ideas and models benefit from up-to-date thinking.
• Support and inspire fellow researchers and peers through detailed feedback and peer group reviews.
• Advanced degree in econometrics, mathematics, finance, economics, accounting, or similar degree
• Academic research experience and/or a PhD a plus
• CFA is a plus
• Independent demonstrated work on research projects. Academic and written papers a plus, with the demonstrated ability to communicate complex concepts easily.
• Sorting, cleaning, and working with large datasets. Pricing and fundamental datasets a must, while higher frequency data and macro datasets a plus. Enjoys getting their hands ‘dirty' with data.
• Working with Matlab\SAS\Python\R or similar analytical packages is necessary experience.
• Programming in an object oriented language is a plus
• Knowledge of Eiffel a plus.
Knowledge and Skills
• Strong analytical and quantitative skills, including advanced econometric techniques, regression (linear and non-linear), and optimisation techniques for portfolio construction.
• Demonstrated knowledge of new signal development and testing, as well as implementation and optimisation methodologies.
• Knowledge of equity markets, including fundamental data sources. Knowledge and familiarity with alternate data, and big data sources is preferable.
• Strong programming skills in statistical and/or data focused languages.
• Databasing skills like SQL a strong plus.
• Rigorous attention to detail
• Strong communication skills
• Ability to think critically about investment issues, and to enjoy solving problems
• Sound judgment - ability to make decisions with imperfect information
• Ability to keep a positive and productive attitude under challenging circumstances
• Self motivated - ability to follow projects through to completion
• Ability to work effectively in a team environment