We are seeking an experienced Quantitative Researcher to join a fast-paced, data-driven technology team. This role will focus on developing and refining real-time machine-learning models that power advanced optimization systems. You will work closely with engineers and fellow quantitative professionals to translate research into scalable production solutions.

Key Responsibilities:
• Design, develop, train, and refine machine-learning models that generate real-time decision signals from high-volume time-series data
• Translate research improvements into production-level optimization logic that enhances system performance and efficiency
• Partner with engineers and quantitative team members on algorithm improvements, performance analysis, and system upgrades
• Contribute to research codebases, including data pipelines, dimensionality reduction, signal filtering, and noise-reduction techniques
• Support testing, validation, and deployment of models in live environments

Qualifications and Experience:
• Experience working with large-scale, high-frequency time-series datasets
• Strong understanding of real-time systems, data flow, and optimization frameworks
• Proficiency in Python and C++
• Proven experience building and deploying machine-learning models
• Strong analytical, quantitative, and problem-solving skills
• Bachelor’s degree in Computer Science, Mathematics, Statistics, Physics, or a related quantitative field; advanced degree preferred
• 7+ years of experience in a high-performance, data-driven research or engineering environment
• Experience with real-time data feeds and complex system architectures
• Exposure to digital asset or distributed systems is a plus

Why Join:
• Work on cutting-edge modeling and real-time optimization problems
• Collaborate with highly technical, research-driven teams
• Competitive compensation and long-term growth opportunities
• Flexible hybrid and remote work arrangements