Quantitative Research & Technology – All Levels
Newbridge
- Abu Dhabi
- Permanent
- Full-time
We look for three core traits, often in the same person: * Scientific Mindset: You're driven by hypotheses, data, and evidence. You value intellectual honesty, careful experimentation, and the discipline to let results — not ego — decide what works.
- Technical Excellence: You build. Whether it's research code, production systems, or novel data pipelines, you have exceptional skills in technology and development and take pride in craftsmanship.
- Problem-Solving Grit: You approach open-ended challenges with curiosity and persistence. You're comfortable with ambiguity, you decompose complexity, and you iterate until you crack it.
You'll join a collegial, multidisciplinary team where mathematicians, physicists, computer scientists, statisticians, and engineers work side by side. Deep experts complement each other's skills, share knowledge openly, and invest in each other's professional growth. Ideas win on merit. Bureaucracy loses. We optimize for learning velocity and impact.What You'll Work On
While roles differ by team and level, common themes include:
- Research: Formulate and test new hypotheses using large, complex datasets. Develop models and signals grounded in statistics and economic intuition.
- Technology: Design and build the data, compute, and trading infrastructure that lets us research faster and deploy strategies reliably.
- Implementation: Translate research into production. Ensure strategies are robust, scalable, and continuously monitored.
- Education: An advanced degree in a STEM discipline — Science, Technology, Engineering, or Mathematics — is preferred. Bachelor's with exceptional track record also considered.
- Experience: We're recruiting across all levels. Whether you're finishing a PhD, 2 years into industry, or 15 years into leading teams, show us what you've built and what you've learned.
- Skills: Demonstrated excellence in one or more of: quantitative research, statistical modeling, software engineering, distributed systems, data engineering, or ML. Clear, logical communication is essential.
- Attributes: Intellectual curiosity, high ownership, low ego, and a bias for action. You should be energized by peer review and fast feedback loops.
- Domain Knowledge: No prior investment or finance experience is required. We hire for talent and teach you the markets.
In your application, please highlight three things: * Your education and training — formal and self-directed.
- Your experience — projects, research, or systems you're proud of.
- What makes you brilliant — the specific way you think, build, or solve problems that's different from others.