Paris Intern Researcher: Quant Analytics & Data Science

Machina Capital; Paris; Sur place; EUR 11 000 - 22 000; Plein temps

Résumé du poste

Machina Capital is seeking an Intern Researcher to join our Paris-based team. You will analyze large datasets, help design and backtest systematic investment models, and explore new data sources to inform trading strategies.

You will collaborate with quantitative researchers and portfolio managers, staying abreast of advances in quantitative finance, data science, and machine learning to identify practical applications for our strategies.

Qualifications

• Strong academic background in applied mathematics, statistics or related quantitative field.
• Experience or strong interest in programming, particularly in Python, C# or similar languages.
• Solid understanding of probability, statistics, and data analysis techniques.
• Passion for exploring complex modeling problems and solving them rigorously.
• Creativity, curiosity, and critical thinking (and ability to debate about any topic with team members during morning coffees).
• Strong teamwork and communication skills, with the ability to collaborate in a dynamic environment.
• Familiarity with financial markets or trading strategies is a plus, but not required.

Responsabilités

• Analyzing large datasets to uncover patterns and insights that can inform trading strategies.
• Assisting in the design, backtesting, and optimization of systematic investment models.
• Exploring new data sources and integrating them into existing research workflows.
• Collaborating with quantitative researchers and portfolio managers to implement research ideas in production.
• Staying updated on the latest advancements in quantitative finance, data science, and machine learning to identify potential applications for our strategies.

Connaissances

Python

C#

Statistics

Data analysis

Teamwork

Formation

Applied mathematics

Description du poste

Machina Capital is seeking an Intern Researcher to join our Paris-based team. You will analyze large datasets, help design and backtest systematic investment models, and explore new data sources to inform trading strategies.

You will collaborate with quantitative researchers and portfolio managers, staying abreast of advances in quantitative finance, data science, and machine learning to identify practical applications for our strategies.