What are the responsibilities and job description for the Quant Strategist- Credit position at Clear Point Group?
Role Summary
We are looking for a Quantitative Strategist to work alongside credit portfolio managers, helping translate data into actionable investment ideas and improving trading outcomes. This role is heavily research-oriented, requiring strong analytical thinking, thoughtful hypothesis development, and disciplined validation of results. The ideal candidate will be comfortable working in a fast-paced front-office hedge fund environment and communicating complex findings in a clear, practical way.
Key Responsibilities
- Modernize and transition existing desk tools from spreadsheet-based processes into robust Python-driven systems
- Support portfolio managers by enhancing trading workflows and identifying opportunities for process improvement
- Analyze large and diverse datasets (market, macroeconomic, and alternative data) to uncover insights relevant to credit strategies
- Contribute to the development of reporting frameworks for P&L, risk, and performance attribution
- Collaborate on quantitative research initiatives tied directly to investment decisions
- Partner with the broader quant team to design and implement scalable backtesting and data analysis capabilities
- Develop visualization tools to support research, signal evaluation, and portfolio monitoring
- Streamline and automate research pipelines and elements of the trading lifecycle
Qualifications & Experience
- Bachelor’s degree in a quantitative discipline (e.g., Mathematics, Engineering, Computer Science); advanced degree is a plus
- 5 years of experience in a front-office quantitative, research, or trading support role
- Solid understanding of credit markets, including investment grade, high yield, and CDS, with familiarity in spread measures, curve dynamics, and relative value analysis
- Knowledge of fixed income analytics such as duration, carry, roll-down, and curve construction
- Exposure to structured credit products (e.g., CLOs, ABS, RMBS) and related modeling concepts is beneficial
- Strong programming skills in Python, including experience with key data science libraries; ability to write clean, maintainable code
- Familiarity with modern development tools and environments
- Experience working with large datasets and developing predictive or analytical models
- Strong communication skills, with the ability to present technical work to both quantitative and non-technical stakeholders
Salary : $150,000 - $250,000