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Quantitative Analyst

2 months ago

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Position: Quantitative Researcher (Full-Time - PhD+)

As a Quantitative Researcher at Radix Trading LLC, your primary responsibility will be to uncover trading opportunities. Your strong quantitative abilities, combined with coding skills, will enhance the innovation process and enable your colleagues to utilize your findings effectively.


Throughout a diverse range of projects over a six-month timeframe, you will acquire valuable insights into market dynamics, trading methodologies, and our proprietary research infrastructure.

We have eliminated barriers to access within our organization, allowing you to immerse yourself in the complexities of our industry while making significant contributions that impact our performance from the outset.

While a passion for trading is essential, a financial background is not a prerequisite. Our team predominantly comprises individuals from academic backgrounds—professors, postdoctoral researchers, PhDs, and undergraduates—rather than professionals from trading firms. We value mental diversity and annually recruit a select group of scholars from various disciplines.


Recent additions to our research team have connections to prestigious institutions such as Harvard, MIT, Cambridge, Princeton, Yale, IAS, UPenn, Stanford, Washington, UChicago, Caltech, and others.


COMPENSATION: We offer a competitive salary along with a quarterly bonus contingent on individual performance and contributions to the success of the team and the firm.

Qualifications:

We seek highly analytical individuals (with backgrounds in mathematics, physics, computer science, statistics, electrical engineering, etc.) who aspire to contribute to the development of a research-driven trading firm.


Key Attributes Required:

  • Persistent Drive to Improve: A natural inclination to strive for excellence, even after achieving significant milestones.
  • Creative Problem Solving and Probabilistic Thinking: A passion for learning and swiftly applying new concepts, integrating knowledge from various fields to generate innovative ideas, and employing a data-driven, probabilistic approach to testing and implementing these ideas.
  • Team Mindset: A commitment to enhancing team performance through collaboration and idea-sharing, recognizing that collective success surpasses individual achievements.
  • Mental Flexibility & Self-Awareness: The ability to adapt frequently based on new data, results, and feedback regarding trading ideas and personal performance.
  • Orientation for Generating Profit: While we appreciate academic training, our work transcends academic exercises. We adopt a pragmatic approach to testing ideas, prioritizing projects that promise high returns and focusing our efforts on creating substantial value for the firm.

Research / Quantitative Trading Strategy Skills:

  • Strong intuition and analytical thinking with data sets, capable of designing new alphas and understanding complex systems.
  • Demonstrated ability to quickly analyze data to identify empirical relationships and differentiate between noise and signal.
  • Familiarity with classical statistical methods, with the ability to rigorously apply them and a willingness to learn new techniques to address challenges.
  • Experience with modern AI methodologies or a desire to engage in Applied Machine Learning projects is advantageous.
  • A relentless curiosity about finance and trading data, coupled with motivation to seek answers, even when faced with the absence of correlation or signal.
  • Experience in establishing research frameworks and executing projects.
  • Understanding of financial products, market dynamics, and microstructure.
  • Proficiency in low-level programming languages such as C++, Python, or Java, with an awareness of the strengths of specific languages and the ability to tackle complex problems through a nuanced understanding of these languages.

Application Requirements:

  • Please upload your unofficial undergraduate transcript.
  • Please upload your unofficial graduate transcript.
  • Please upload any additional transcripts.
  • Do you require employer-sponsored work authorization?
  • Do you have a preferred office location?
  • Please indicate the year you expect to complete your current university degree or position.
  • Please indicate the month you expect to complete your current university degree or position.
  • What is your current affiliation with your university?