VP of Quantitative Trading Technology

Company Description CMG Nexus is a dynamic venture platform founded by professional footballer Cody Gakpo, operating at the intersection of sports, entrepreneurship, and innovation. The organization brings values from the pitch—discipline, teamwork, and resilience—into business initiatives, focusing on brand representation, strategic partnerships, new ventures, and startup investments. Trust is a core principle, guiding relationships with partners, collaborators, and team members. CMG Nexus believes that performance-driven skills from sports translate directly into business success, connecting ambition with opportunity to create positive impact across industries.
Role Description The VP of Quantitative Trading Technology is a full-time remote role responsible for leading the design, implementation, and optimization of quantitative trading systems across multiple asset classes. This role oversees the development of trading algorithms, infrastructure, and tools that enable data-driven decision-making and scalable execution. Day-to-day responsibilities include collaborating with traders and quantitative researchers to translate trading strategies into robust technology solutions, managing technical roadmaps, and ensuring system reliability, performance, and security. The VP will coordinate backtesting frameworks, data pipelines, and real-time analytics, while establishing best practices in coding standards, documentation, and deployment. This position also involves mentoring technology team members, partnering closely with finance and risk stakeholders, and contributing to long-term trading innovation aligned with CMG Nexus’s entrepreneurial vision.
Qualifications
Strong expertise in trading strategies and trading, with experience designing, implementing, and evaluating quantitative models.
Knowledge of equities markets and related instruments, including market microstructure and execution considerations.
Advanced analytical skills and finance knowledge, with ability to interpret complex data sets and translate insights into actionable technology solutions.
Proficiency in programming languages commonly used in quantitative trading (e.g., Python, C++, or Java) and experience with data engineering and distributed systems.
Background in algorithmic execution, backtesting frameworks, and risk management tools for quantitative trading environments.
Demonstrated leadership experience managing technical teams, setting strategic direction, and delivering production-grade trading systems.
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Finance, or a related quantitative discipline.
Ability to work effectively in a remote, cross-functional environment, with clear communication, collaboration, and accountability.
Experience in startup or entrepreneurial settings is a plus, as well as interest in the intersection of technology, sports, and innovation.

Work arrangement
Yes