|THE COMPANY: 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.
HOW TO APPLY: please, send your CV together with a motivational letter to email@example.com