Pendal has announced the appointment of machine learning quantitative analyst, Itay Feldman, who will help integrate machine learning into bonds, income and defensive strategies investment process.
Feldman, who was recruited initially on a one year basis, would focus on utilising machine learning algorithms to provide a layer of filtering and analysis over the team’s current suite of quantitative models.
He would join bond, income and defensive strategies boutique, led by Vimal Gor.
Prior to this, Feldman worked for Advantage Data where he was a data scientist. He also worked in New York City as an investment banker with MR Beal & Co and Ramirez & Co where he specialised in building bond optimisation models, fixed income and swap pricing models.
“We believe that investment markets are entering a period of secular change and we are constantly looking at ways to improve and evolve our invest process to prepare for this change.
“I believe that it is inevitable that machine learning will be embedded into investment decision making processes, the only questions are when to do it, and how.”