Quantitative Research Analyst Internship

SCM

Radnor (Delaware County)

On-site

USD 27,552 - 41,328

Part time

14 days+

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Job summary

A financial research firm located in Radnor is seeking motivated students for a Quantitative Research Analyst Internship. This opportunity emphasizes empirical research in the financial markets. Responsibilities include analyzing academic research and conducting statistical analysis on data sets. Ideal candidates should be pursuing a degree in quantitative disciplines with programming skills in R, C++, or Python. This internship allows for both summer and part-time commitments during the academic year.

Qualifications

  • Graduate-level degree in statistics, econometrics, mathematics, engineering, physics, computer science, or finance required.
  • Experience in regression analysis and programming.
  • Strong interest in building and analyzing large data sets.

Responsibilities

  • Analyze academic research related to global financial market anomalies.
  • Build data sets and perform statistical analysis.

Skills

Programming experience (R, C++, Python)
Regression analysis
Organizational skills
Communication skills
Interest in data analysis

Education

Substantial progress toward a degree in a quantitative discipline

Job description

Quantitative Research Analyst Internship

Radnor, PA

We're seeking exceptionally motivated students with a strong interest in the financial markets to contribute to our empirical research process. The range of research ideas to investigate is open-ended and will depend on a candidate's background and strengths.

Opportunities, including full-time summer internships and part-time work throughout the school year, are available for qualified students at each of the undergraduate, masters and PhD levels.

Primary Responsibilities
  • Read and analyze academic research or other source material pertaining to anomalies in the global financial markets.
  • Build data sets and conduct statistical analysis on the data.
Requirements
  • Substantial progress toward a degree (graduate level preferred) in a quantitative discipline (e.g. statistics, econometrics, mathematics, engineering, physics or computer science) or finance (with extensive coursework in quantitative disciplines).
  • Programming experience, ideally including R, C++ and/or Python.
  • Experience with regression analysis.
  • Strong interest in learning how to build, organize and analyze large data sets.
  • Strong organizational and communication skills.
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