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Decision Analyst

4 months ago

United Kingdom Investment Management Partners Full time

Our client is a global Investment Management firm with over $ 30 billion in AUM. The investment philosophy upheld by the client is fundamental, long-term, and contrarian. Operating as contrarian investors, they strive to adopt a distinct perspective that permeates all aspects of their approach.

Their Decision Analytics team comprises Data Analysts and Behavioral Science experts who utilize cutting-edge technology and behavioural science methodologies to extract personalized insights from an extensive dataset. These insights are instrumental in enhancing investors' decision-making processes and ultimately driving superior outcomes for their clients.

Key Responsibilities:

  • Conduct in-depth statistical research (primarily in R) on data generated by stock pickers throughout their decision-making cycles.
  • Articulate data-backed insights to investment decision-makers in a clear and concise manner.
  • Collaborate with the development team to prototype decision analysis tools that offer actionable feedback to investment teams.
  • Utilize advanced statistical techniques and modelling to identify and interpret patterns in actions and outcomes.
  • Work closely with behavioural science experts to provide quantitative evidence in applying behavioural concepts to real-world business challenges.
  • Gain a deep understanding of the processes utilized by investment analysts and portfolio managers to effectively support and optimize their potential for generating superior returns for clients.

Experience:

  • Degree in Quantitative Finance, Mathematics, Statistics, Physics, Computer Science, or a related field.
  • Strong quantitative skills with proficiency in statistical analysis and coding (Python, R).
  • Experience in applying quantitative methods to financial data analysis.
  • Exhibited excellence in academic and/or extra-curricular activities.
  • A demonstrated interest in investing, and/or unconscious biases is an advantage.