Quantitative Researcher: Build Predictive Signals & ML Models

Qube Research & Technologies; Paris; On-site; EUR 90,000 - 120,000; Full time

Job summary

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager. We are a technology and data driven group implementing a scientific approach to investing.

You will create high quality predictive signals, identify statistical patterns across large datasets, and lead the full research cycle from signal generation to implementation. You will share results with researchers, implement signals in the execution platform, and monitor model performance across time with

Qualifications

• Advanced degree in a quantitative field (e.g., data science, statistics, mathematics, physics, engineering).
• Strong knowledge in statistics, machine learning, NLP or AI techniques is a plus.
• Capacity to multi-task in a fast-paced environment with attention to detail.
• Coding skills in at least one leading language (Python, R, Matlab and/or C++, C#).

Responsibilities

• Create high quality predictive signals leveraging large, diverse datasets.
• Identify statistical patterns and opportunities across data.
• Share and discuss research results, methodology and data with other researchers.
• Implement signals and datasets within the global execution platform.
• Monitor signal behavior and model performance over time.
• Lead the full strategy research cycle from signal generation to implementation.

Skills

Statistics

Machine Learning

NLP

Programming (Python)

Programming (R)

Programming (Matlab)

Programming (C++)

Programming (C#)

Big data analysis

Data exploration

Communication

Autonomy

Education

Advanced degree in quantitative field

Job description

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager. We are a technology and data driven group implementing a scientific approach to investing.

You will create high quality predictive signals, identify statistical patterns across large datasets, and lead the full research cycle from signal generation to implementation. You will share results with researchers, implement signals in the execution platform, and monitor model performance across time with