Quantitative Analyst at cega

Job Description

Key Responsibilities

• Lead the quantitative effort by developing and implementing stable, scalable, and robust models for multi-underlying exotic products, ensuring they meet regulatory and operational standards.
• Create and maintain a comprehensive risk management framework that includes the calculation and monitoring of Greeks (delta, gamma, vega, theta, rho), conducting stress tests under various market scenarios, and producing detailed risk analysis reports to support trading decisions.
• Design and implement backtesting frameworks for systematic digital asset strategies, incorporating historical data and advanced statistical techniques to evaluate performance metrics such as Sharpe ratio, maximum drawdown, and volatility.
• Collaborate with cross-functional teams, including traders, portfolio managers, and data scientists, to align quantitative models with business objectives and market conditions.
• Continuously refine and optimize existing models and frameworks to improve accuracy, efficiency, and adaptability to changing market dynamics.
• Document all model development processes, risk analysis methodologies, and backtesting procedures to ensure transparency and reproducibility.
• Communicate findings and recommendations to stakeholders through clear and concise presentations, reports, and data visualizations.
• Stay updated on industry trends, regulatory changes, and emerging technologies to incorporate best practices into quantitative workflows.

Job Requirements

• Master's or Ph.D. in Quantitative Finance, Mathematics, Statistics, or a related field, with a strong academic background in financial modeling and risk analysis.
• Proven experience in developing quantitative models for complex financial instruments, preferably with a focus on exotic derivatives and digital assets.
• Expertise in risk management methodologies, including the calculation of Greeks, stress testing protocols, and risk analysis frameworks, with a demonstrated ability to produce actionable insights.
• Proficiency in programming languages such as Python, R, or C++, with experience in developing and maintaining backtesting frameworks for systematic trading strategies.
• Strong analytical skills and attention to detail, with the ability to interpret complex financial data and identify patterns or anomalies.
• Excellent communication skills, both written and verbal, to effectively convey technical findings to non-technical stakeholders and collaborate with cross-functional teams.
• Ability to work independently and as part of a team, with a proactive approach to problem-solving and a commitment to continuous learning and improvement.
• Experience with financial data analysis tools and platforms, such as Bloomberg, MATLAB, or SQL, is a plus.
• Knowledge of regulatory requirements and compliance standards in the financial industry is preferred.
• Strong organizational skills and the ability to manage multiple projects simultaneously, with a focus on meeting deadlines and maintaining high-quality outputs.