Quantitative Research Scientist, Finance & Data

Point72; Paris; Sur place; EUR 90 000 - 140 000; Plein temps

Résumé du poste

Cubist Systematic Strategies, an affiliate of Point72, seeks researchers to independently conduct quantitative finance research with a focus on statistical and predictive models. You will manage all steps from methodology selection to backtesting, data collection, and performance monitoring, collaborating with portfolio managers and researchers.

You’ll thrive if you enjoy heavy data work, rigorous testing, and translating complex analyses into actionable investment ideas for a demanding

Qualifications

• MS or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline.
• 3-7 years of experience in alpha driven quantitative research for equities, futures, fixed income, credit, and/or FX.
• Strong analytical and quantitative skills.
• Demonstrated ability to conduct independent research utilizing large data sets.
• Programming in C++, Java, C#, MATLAB, R, Python, or Perl.

Responsabilités

• Independently conduct quantitative finance research focusing on statistical and predictive models.
• Manage all aspects of the research process: methodology selection, data collection and analysis, testing, prototyping, backtesting, and performance monitoring.
• Collaborate with portfolio managers and researchers to translate findings into investment insights.

Connaissances

Analytical skills

Quantitative skills

Independent research

Problem solving

Ownership

Formation

MS or PhD candidates in quantitative discipline

Outils

C++

Java

C#

MATLAB

R

Python

Perl

Description du poste

Cubist Systematic Strategies, an affiliate of Point72, seeks researchers to independently conduct quantitative finance research with a focus on statistical and predictive models. You will manage all steps from methodology selection to backtesting, data collection, and performance monitoring, collaborating with portfolio managers and researchers.

You’ll thrive if you enjoy heavy data work, rigorous testing, and translating complex analyses into actionable investment ideas for a demanding