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C

Systematic Investment Research

Cooper Fitch

Location

Remote

Salary

Not specified

Type

fulltime

Posted

Today

via linkedin

Job Description

Our client is building a team of researchers who want to push the boundaries of quantitative investing.

This isn't a traditional quant role

We're looking for scientists, researchers and innovators who believe the next generation of investment strategies will be discovered through rigorous scientific research, mathematical innovation and machine learning.

You'll work alongside researchers exploring new ideas across systematic investing, quantitative finance and financial data science—developing novel methodologies that can ultimately become live investment strategies.

What You'll Do

  • Conduct original quantitative research into systematic investment strategies.
  • Develop and test new hypotheses using machine learning, statistics and mathematical modelling.
  • Design novel alpha signals, portfolio construction techniques and optimisation frameworks.
  • Research financial markets using large-scale structured and alternative datasets.
  • Build robust research pipelines, experimentation frameworks and backtesting environments.
  • Validate ideas through rigorous scientific experimentation, out-of-sample testing and reproducible research.
  • Translate successful research into production investment strategies.

What We're Looking For

We're far more interested in how you think than where you've worked. You'll likely have experience in several of the following:

  • Scientific research within quantitative finance, mathematics, statistics, computer science or physics.
  • Original research into systematic investing, portfolio optimisation or financial data science.
  • Machine learning applied directly to investment research.
  • Statistical modelling and experimental design.
  • Developing new quantitative methodologies rather than simply applying existing ones.
  • Python and modern quantitative research tools.
  • Working with large financial or alternative datasets.

Publications, open-source research, conference presentations or contributions to the quantitative research community are highly valued.

Ideal Backgrounds

You might currently be a:

  • Quantitative Research Scientist
  • Systematic Researcher
  • Alpha Researcher
  • Financial Data Scientist
  • Machine Learning Researcher (Investments)
  • Quantitative Portfolio Researcher
  • Applied Research Scientist (Financial Markets)

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