Develop innovative investment ideas using quantitative analysis to capture long-run rewarded sustainable insights
This may include a review of existing data, testing of the usability of new datasets, or leveraging AI, data science or ML methodologies, and back-testing of these strategies and interpretation/implementation of output results to improve our research process
Construct and maintain quantitative investment strategies including portfolio rebalancing oversight
Deliver high quality signal research with a focus on long-only global equities and the usage of novel datasets
Collaborate with research colleagues across the firm on investment ideas, with portfolio managers on efficient execution of ideas and with investment strategists on innovative investment products
Collaborate with wider BlackRock platforms to deliver innovative systematic sustainable solutions

Relevant experience (in academia and/or industry) or internships a plus, but not necessary
Proficiency in at least one programming language such as Python, Matlab or similar
SQL and Unix experience a plus but not necessary
Detailed knowledge of data science and statistical techniques, portfolio optimization, financial economics and risk models
Attention to detail, curious and self-motivated
Highly organized and ability to work towards tight deadlines
Good communication skills: ability to communicate complex ideas clearly to colleagues and clients
Collaborative team player, willing to engage with other colleagues, share ideas and give/receive constructive feedback
The ideal candidate would have a degree in a quantitative field, such as mathematics, econometrics, computer science, or “hard sciences” and a specialization in economics/finance either through coursework/internship or a graduate degree
PhD or equivalent (Post-doc) is a plus

Quantitative Investment Researcher, Associate

Key skills