London - Sustainable Investment Quant (Senior Portfolio Manager)

06/06/2021

Arabesque Asset Management is a sustainable and quantitative investment management business which uses self-learning quantitative models, AI, and big data.

Headquartered in London, Arabesque Asset Management operates across Europe and has offices in Boston and Singapore.

Your Role & Responsibilities

We are excited to offer a position for a Sustainable Investment Quant (Senior Portfolio Manager) to focus on ESG quant equity product development and portfolio management. We are looking for people who are passionate about building state-of-the-art AI-powered ESG equity investments solutions in close collaboration with Arabesque S-Ray and AI and deploy them on our AI investment platform.

Requirements

  • Thorough understanding of all components of the systematic equity investment and research process and different systematic investing approaches
  • Deep knowledge and relevant experience of the investment process (e.g., portfolio construction, risk modelling, strategy analytics, back-testing)
  • Ten year's front-office experience in developing, deploying, and running live quantitative equity investing solutions or components thereof at an asset manager, hedge fund or asset owner
  • Practical experience with portfolio rebalancing and providing portfolio analytics. Full proficiency in the handling of portfolio management
  • Proven track-record of managing a small team of investment specialists and successful collaboration with other stakeholders
  • Good communication skills and relevant experience with client engagement
  • Minimum relevant work experience of 10 years
  • Advanced in Python and familiarity with modern Machine Learning computing ecosystem and tools (Git, cloud computing etc.)
  • Min. MSc degree in a quantitative subject (e.g., engineering, sciences, quantitative finance or similar)

Our nice-to-haves:

  • Good understanding about ESG and alternative data and sustainability investing approaches and landscape.
  • Experience with Machine Learning methods in (parts of) the investment process.
  • CFA accredited.