6 дней назад
Quantitative Risk Analyst (FinTech)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Quantitative Risk Analyst (FinTech): Developing and validating quantitative risk models for CFD asset classes with an accent on VaR, Expected Shortfall, Monte Carlo simulations, stress testing, and real-time monitoring. Focus on calibrating statistical models, validating market and counterparty credit risk models, and translating quantitative outputs into margin, capital-at-risk, and risk-limit frameworks.
Location: Limassol, Cyprus; full-time on-site, Monday to Friday, 09:00–17:00
Company
is a global trading and financial technology company with more than 15 years of experience and an international presence.
What you will do
- Design, implement, calibrate, and validate quantitative risk models across CFD asset classes, including FX, indices, commodities, equities, and crypto.
- Develop anomaly detection, scenario generation, Early Warning Indicator, and real-time risk monitoring models.
- Perform independent validation of market risk, counterparty credit risk, and trading algorithm models.
- Monitor margin rates, run stress tests and scenario analyses, and assess market, credit, liquidity, and operational model risk.
- Maintain model documentation and risk registers while supporting risk governance, exposure limits, drawdown limits, and kill-switch parameters.
- Present risk insights to senior stakeholders and coordinate model deployment with the Quantitative Development team.
Requirements
- Degree in Quantitative Finance, Financial Mathematics, Statistics, Physics, Engineering, Computer Science, or a related field.
- At least 3 years of experience in quantitative model development, validation, or quantitative risk management in financial services or trading; CFD or FX derivatives experience is strongly preferred.
- Strong Python skills with pandas, NumPy, SciPy, scikit-learn, statsmodels, and Jupyter, including experience with large, high-frequency financial datasets.
- Strong foundation in probability theory, mathematical statistics, stochastic processes, and time-series econometrics.
- Knowledge of market microstructure and market risk models including VaR, Expected Shortfall, Greeks, implied volatility, and Monte Carlo, plus counterparty credit risk concepts such as PD, LGD, EL, and UL.
- SQL experience is strongly preferred; FRM or CFA certification is advantageous.
Culture & Benefits
- 22 days of annual leave and 12 paid sick days.
- Medical insurance, group savings, and life insurance after six months.
- Paid overtime, learning and development budgets, and career growth support.
- Daily lunch buffet, stocked kitchen, gym facilities, sports, and spa treatments.
- Employee discounts, referral bonuses, team events, and regular social activities.
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