Remote Lead Quantitative Analyst — Drive Alpha

Placements24; Randburg; Hybrid; ZAR 1,800,000 - 3,000,000; Full time

Benefits offered by this job

Top-tier compensation with performance

Fully remote work

Stock options or profit-sharing

Access to cutting-edge research tools

Job summary

Placements24 is seeking an experienced Lead Quantitative Analyst to spearhead research and development of mathematical models for trading, risk, and derivatives pricing. The role is fully remote, allowing global collaboration with traders and portfolio managers and leading a team of analysts.

You will mentor juniors, drive alpha generation, backtest rigorously, and implement cutting-edge techniques in ML, econometrics, and statistics, with a focus on robust, scalable systems.

Qualifications

• Ph.D. or Master's in a quantitative field (Math, Stats, Physics, CS, or Financial Engineering).
• At least 7 years of quantitative finance experience with trading or risk models.
• Expert in Python, C++, or R with relevant libraries.
• Strong knowledge of derivatives pricing, portfolio optimization, and risk management.
• Proven leadership and ability to mentor a team.

Responsibilities

• Lead design and deployment of quantitative models for markets.
• Mentor a team of quantitative analysts and guide career development.
• Collaborate with traders, PMs, and risk managers to translate needs.
• Backtest and analyze performance of trading strategies.
• Research cutting-edge methods in ML, statistics, and econometrics.
• Ensure robustness and efficiency of all systems.

Skills

Leadership

Quantitative modeling

Mentoring

Education

PhD or Master's in quantitative field

Tools

Python

C++

R

Job description

Placements24 is seeking an experienced Lead Quantitative Analyst to spearhead research and development of mathematical models for trading, risk, and derivatives pricing. The role is fully remote, allowing global collaboration with traders and portfolio managers and leading a team of analysts.

You will mentor juniors, drive alpha generation, backtest rigorously, and implement cutting-edge techniques in ML, econometrics, and statistics, with a focus on robust, scalable systems.