Researcher-in-training ARPM

ARPM – Advanced Risk and Portfolio Management is a privately held research institution, directed by Attilio Meucci, based in New York City with virtual offices world-wide. ARPM's mission is to set and disseminate the standards for advanced quantitative risk management and portfolio management across the financial industry: asset management, banking, and insurance.

The opportunity 

ARPM is looking for a new researcher-in-training for a minimum period of 6 months, indefinitely extensible. The successful candidate will review and code practical case studies and theoretical examples in quantitative finance, contributing to the ARPM Lab. The successful candidate will work full-time, remotely, constantly communicating via multi-media with the other members of ARPM.

The ARPM researcher-in-training position represents a great opportunity for candidates with strong academic background, who wish to apply to real problems in finance the rigorous, research-oriented approach acquired in their schooling.

The progression

ARPM emphasizes the constant intellectual growth of its resources. For the first 6 months the researcher-in- training will be focused on specific projects. At the end of this period (s)he will conduct a presentation on the topics covered.

Then, (s)he will start broadening his/her scope, attending the presentations of their peers and seniors, working on broader projects, and acquiring hands-on- knowledge of all the topics of the ARPM Lab. The approximate time required to attain the required level of familiarity with the ARPM Lab is: two years for a recent master's graduate; one year for a recent PhD graduate.

When ready, the researcher-in-training will be tested on all such topics with an exam. If successful, (s)he will conclude his/her training period, attaining the title of ARPM researcher. The ARPM researcher will then engage in highly quantitative projects with ARPM clients, becoming a profit center.

The candidate

  • Master's degree in mathematics, physics, engineering, computer science, statistics, data science, quantitative economics.
  • PhD in hard sciences or master's degree in quantitative finance is a plus.
  • Very strong command of foundational mathematics, including multivariate calculus and linear algebra.
  • Good knowledge of statistics and probability.
  • Proficiency in MATLAB, Python, or similar programming languages.
  • Good command of English.



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Glavni kontakt:
e-pošta: info.stat (at)

Kontakt za administrativna vprašanja (vpis, tehnična vprašanja):
Tanja Petek
Univerza v Ljubljani, Fakulteta za elektrotehniko, Tržaška cesta 25, 1000 Ljubljana.
št. sobe: AN012C-ŠTU
telefon: 01 4768 460
e-pošta: tanja.petek (at)