Quantitative Python Developer

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets.

We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies.

Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform.

WorldQuant is built on a culture that pairs academic sensibility with accountability for results.

Employees are encouraged to think openly about problems, balancing intellectualism and practicality.

Excellent ideas come from anyone, anywhere.

Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement.

Our goal is to hire the best and the brightest.

We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent.

There is no roadmap to future success, so we need people who can help us build it.

Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers.

Our environment is relaxed yet intellectually driven.

We seek people who think in code and are motivated by being around like-minded people.

The Role: WorldQuant is seeking an exceptional individual to work as a Quantitative Developer in a high performance business-embedded tech team.

Working closely with Technologists and Researchers, building complex data pipelines and frameworks for strategy and performance analytics.

A successful candidate will bring a strong quant dev skillset with the best design / implementation principles and ability to quickly acquire in-depth domain knowledge.

• 5+ years of hands-on experience as a developer
• Strong Data Structures, Algorithms, and Maths fundamentals
• Knowledge of Python and Linux/Unix platforms; familiarity with scripting languages.
• Familiarity with technologies related to data processing such as numpy, pandas, Airflow, Kubernetes, etc.