Quantitative Engineer

Role Summary

Quantitative Engineer

We are seeking a Quantitative Engineer to help build and enhance our research infrastructure and improve our existing suite of models. The ideal candidate is a mid-level engineer with extensive software development experience in a highly data-driven industry such as finance, technology, or machine learning. The ability to collaborate across teams and support multiple projects is essential.

Responsibilities

• Design scalable systems to support Massar’s quantitative research program.
• Develop high-performance platforms for quantitative research.
• Write comprehensive documentation and conduct code reviews.
• Promote and uphold firm-wide best coding practices.

Requirements

• Degree in computer science or a related field.
• Development experience with AWS or other cloud providers.
• 2+ years of Python experience, including proficiency with libraries such as NumPy, Pandas, PyTorch and TensorFlow.
• Excellent communication skills, self-starter, quick learner, positive attitude, and team player
• Experience in at least one of the following areas:
• Econometrics, factor analyses, or automated trading.
• Weather data modeling.
• Machine learning techniques, such as neural networks.
• Robotics and/or sensor networks.
• Other high-dimensional, computationally intensive data problems.

The all-inclusive salary for this position STARTS at EUR 95.000,00. Competitive and performance-based compensation package, depending upon qualifications.

About the Company

FIRM OVERVIEW

Massar Capital Management, LP (“Massar”) is an alternative investment management company founded in 2015. We employ a global macro trading strategy that seeks to capture investment opportunities across commodity, foreign exchange, fixed income, equity, and derivatives markets. With offices in the United States and Europe, Massar prides itself on its dynamic, entrepreneurial culture. Our investment philosophy combines fundamental understanding of individual assets with a quantitative, data-driven process. We build proprietary technology and develop statistical methods to leverage both public and in-house data sets. Our team members possess strong technical skills, a passion for problem-solving, and an intellectual curiosity about financial markets.