JPMorgan has been consistently ahead of the curve when it comes to applying artificial intelligence (A.I.) to the banking industry. From its massive report on machine learning and Big Data in finance a few years ago, to the launch of the reinforcement-learning LOXM equity trading algorithm in 2017, to LOXM’s evolution into “Deep X,” which assists the bank’s equities algos globally, JPMorgan is actually using A.I. to trade. (Which is more than can be said for most of its rivals.)
If you’re interested in working in artificial intelligence in banking and finance, therefore, JPMorgan is building a reputation as the place to be, not the least since recruiting Dr. Manuela Veloso to set up its internal A.I. research group in 2018. Alongside her job at JPMorgan, Veloso remains the head of machine learning research at Carnegie Mellon University, one of the top-ranked institutions for computer science and A.I.
In this sense, JPMorgan is offering the best of both worlds to top-shelf researchers: The chance to remain in academia whilst also applying ideas commercially.
Interestingly, then, JPMorgan is currently advertising a New York-based job for a ‘research scientist,’ who will be tasked with “exploring and advancing cutting-edge research in the fields of A.I. and Machine Learning, as well as related fields like cryptography.” Insiders say this is a job on Veloso’s team, and the description of what you’ll be up to sounds far more academic than the average IT role in the banking sector (A.I.-focused or not).
According to the job description, JPMorgan’s ‘research scientists’ get to “conduct primary end-to-end research” within a “specialized focus area,” and work with external researchers such as universities. JPMorgan will make sure they have both the hardware and the data infrastructure required.
Given the job spec, you might think JPMorgan’s A.I. research scientists would need a PhD, but this is not the case. The minimum requirement is a bachelor’s degree in computer science, mathematics, statistics, or science and engineering, plus programming skills (Python/Java/C++), plus knowledge of machine learning platforms such as TensorFlow and PyTorch.
In this sense, a job in JPMorgan’s A.I. research team looks like a good deal: You gain exposure to top academics in the machine learning field whilst conducting your own research and getting paid. By comparison, Carnegie Mellon’s Masters in Machine Learning costs $49,000 a year.
This article originally appeared in eFinancialCareers.