Senior Quantitative Researcher - Portfolio Modeling

Senior Quantitative Researcher - Portfolio Modeling

Full-Time 60750 - 74250 Β£ / year (est.) No working from home possible
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At a Glance

  • Tasks: Build complex portfolio models and design innovative investment solutions.
  • Company: Join Robinhood, a leading fintech company revolutionising investing in the UK.
  • Benefits: Attractive salary, flexible working options, and opportunities for professional growth.
  • Other info: Collaborative environment with a focus on innovation and continuous improvement.
  • Why this job: Shape investment products and make a real impact in the finance world.
  • Qualifications: Strong background in quantitative research and data analysis skills.

The predicted salary is between 60750 - 74250 Β£ per year.

Robinhood in the United Kingdom is seeking a Staff Data Scientist (Quantitative Researcher) to report to the Chief Investment Officer and help shape our investment product offerings.

You will build complex portfolio construction factor models and design high-performing investment solutions.

You will collaborate with Product, Engineering, Compliance and Legal to launch these products to customers, backtest models, and continuously improve methodologies using large datasets and advanced statistics.

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Senior Quantitative Researcher - Portfolio Modeling employer: Robinhood

Robinhood is an exceptional employer that champions innovation and collaboration, particularly in its UK office where the Global Product Marketing Manager will thrive. With a strong focus on employee growth, the company offers unique opportunities to work alongside diverse teams in a dynamic environment, fostering both personal and professional development while driving impactful product marketing strategies in expansion markets.

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Contact Details:

Robinhood Recruitment Team

We think you need these skills to ace Senior Quantitative Researcher - Portfolio Modeling

Portfolio Construction
Factor Models
Investment Solutions Design
Collaboration
Backtesting
Methodology Improvement
Large Dataset Management