Quantitative Risk Analyst (PhD)

Company Description Paraclete Capital is the investment manager of the Paraclete Advanced Diversified Alpha fund (PANDA), a systematic alternative risk premia strategy. The firm focuses on data-driven, quantitative approaches to capturing diversified alpha across global markets. Paraclete Capital Pte. Ltd. is a Capital Markets Services-licensed investment management company regulated by the Monetary Authority of Singapore. The team operates at the intersection of quantitative research, risk management, and portfolio implementation, offering opportunities to work with sophisticated institutional-grade strategies. Prospective team members will join a growing, rigorously analytical environment with direct exposure to systematic investing.

Role Description The Quantitative Risk Analyst (PhD) will work on-site in Singapore / Hong Kong in a full-time capacity. Ability to relocate to Hong Kong is preferred. This role is responsible for designing, implementing, and maintaining quantitative risk models for the PANDA strategy, including market risk measurement, stress testing, and scenario analysis. The analyst will monitor portfolio exposures, analyze risk-adjusted performance, and propose risk limits or hedging strategies in collaboration with portfolio managers and researchers. Day-to-day tasks include developing statistical tools, validating model assumptions, documenting methodologies, and producing clear risk reports and dashboards for internal stakeholders. The role also involves researching new risk premia, evaluating emerging risks in markets and instruments, and contributing to enhancements in the firm's overall risk framework and governance.

Qualifications

• Strong expertise in Market Risk and Finance, with the ability to interpret risk metrics in the context of portfolio construction and trading strategies.
• Advanced Quantitative Analytics skills, including experience with mathematical modeling, optimization, and risk factor decomposition.
• Robust Statistics and Analytical Skills, with proficiency in statistical inference, time-series analysis, and handling large, noisy datasets.
• PhD in a quantitative discipline such as Mathematics, Statistics, Financial Engineering, Physics, Computer Science, or a closely related field.
• Proficiency in programming languages commonly used in quantitative finance (e.g., Python, R, MATLAB, or similar), and familiarity with data management tools.
• Experience with systematic or quantitative investment strategies, alternative risk premia, or hedge fund risk management is highly beneficial.
• Ability to communicate complex quantitative concepts clearly to both technical and non-technical audiences and to collaborate effectively within a small, focused team.
• High level of professional integrity, attention to detail, and commitment to working on-site in Singapore / Hong Kong within a regulated financial environment.