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Open nowFirst seen 3 days ago

Chief Quantitative Officer

thehivecareers.co2,874 open roles

Where
Georgetown, Guyana, Remote
Work mode
Remote
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Your applicationOpen nowChief Quantitative Officerthehivecareers.co · Georgetown, Guyana, Remote

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The clock on this job

Early applications get read.

12.1% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.1%7 days
  4. 19.1%14 days
  5. 35.6%30 days
  6. 52.7%60 days
This job: first seen 3 days ago

The posting

Position Overview:

The Chief Quantitative Officer is responsible for leading the development and application of quantitative models, analytics, and data-driven strategies across the organization. The CQO oversees quantitative research, model development, and advanced analytics to support trading, risk management, portfolio optimization, and strategic decision-making. This role requires deep expertise in quantitative finance, data science, and financial modeling.

Key Responsibilities:

1. Quantitative Strategy & Innovation

Develop and implement quantitative strategies to enhance trading, investment, and risk management capabilities.

Drive innovation through advanced analytics, machine learning, and data science techniques.

Align quantitative initiatives with business and investment objectives.

2. Model Development & Validation

Oversee the design, development, and validation of quantitative models (pricing, risk, forecasting, and optimization).

Ensure model accuracy, robustness, and scalability.

Establish model governance frameworks and validation processes.

3. Data Analytics & Infrastructure

Lead the development of data infrastructure and analytics platforms.

Ensure availability, quality, and integrity of data used in quantitative models.

Collaborate with IT and data teams to enhance data capabilities.

4. Risk Management & Analytics

Develop models for market risk, credit risk, liquidity risk, and stress testing.

Support enterprise risk management through quantitative insights.

Monitor model risk and ensure compliance with internal and regulatory standards.

5. Trading & Investment Support

Provide quantitative support for trading strategies, algorithmic trading, and portfolio optimization.

Develop tools for pricing, hedging, and execution.

Collaborate with trading, investment, and portfolio management teams.

6. Research & Development

Lead quantitative research initiatives on financial markets, asset pricing, and emerging technologies.

Stay updated on advancements in quantitative finance, AI, and machine learning.

Publish insights and contribute to thought leadership where appropriate.

7. Reporting & Decision Support

Develop dashboards and reporting tools for performance, risk, and analytics.

Provide data-driven insights to senior management and the Board.

Support strategic planning and business decisions through analytics.

8. Leadership & Team Development

Lead and mentor quantitative analysts, data scientists, and model developers.

Build a high-performance culture focused on innovation and technical excellence.

Drive continuous learning and development in advanced analytics.

9. Compliance & Governance

Ensure adherence to regulatory requirements related to model risk and data usage.

Establish governance frameworks for quantitative models and analytics.

Coordinate with risk, compliance, and audit teams.

Qualifications:

Advanced degree (Master's or PhD) in Quantitative Finance, Mathematics, Statistics, Computer Science, Engineering, or related field.

12–15+ years of experience in quantitative finance, data science, or financial modeling roles.

Proven track record in developing and implementing quantitative models and analytics solutions.

Strong programming skills (e.g., Python, R, C++, or similar).

Key Skills and Competencies:

Strong quantitative and analytical skills.

Expertise in financial modeling, statistics, and machine learning.

Leadership and team management capabilities.

Strategic thinking and problem-solving ability.

Strong communication skills to translate complex models into business insights.

Performance Metrics:

Effectiveness and accuracy of quantitative models.

Contribution to trading, investment, and risk performance.

Innovation in analytics and model development.

Data quality and infrastructure efficiency.

Compliance with model governance and regulatory standards.

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