Remote Quantitative Trading Strategist

Placements24; Upington; Hybrid; ZAR 800,000 - 1,200,000; Full time

Benefits offered by this job

Performance bonuses

Profit-sharing

Fully remote

Health insurance (comprehensive)

Professional development budget

Job summary

Placements24 seeks a highly skilled Remote Quantitative Analyst to design and backtest trading strategies from home. You’ll leverage advanced statistics to build profitable algorithms, work with large datasets, and collaborate with portfolio managers on an algorithmic trading desk.

The ideal candidate has a strong quantitative finance background, expert programming skills in Python/C++/R, and deep knowledge of time series analysis, market microstructure, and derivatives.

Qualifications

• Master's or PhD in a quantitative field.
• Proven experience as a Quantitative Analyst in a trading environment.
• Expertise in Python, C++, or R.
• Strong knowledge of statistical modeling, time series analysis, and machine learning.
• Deep understanding of financial markets, derivatives, and trading execution.

Responsibilities

• Design, develop, and implement quantitative trading strategies across various asset classes.
• Conduct rigorous backtesting and statistical analysis of trading algorithms.
• Analyze market data to identify trading opportunities and patterns.
• Collaborate with traders and portfolio managers to optimize strategy performance.
• Develop and maintain high-quality code for trading systems and analytical tools.
• Research and implement new quantitative methodologies and technologies.

Skills

Python

C++

R

Statistical modeling

Time series analysis

Machine learning

Quantitative finance

Education

Master's or PhD in a quantitative field

Tools

Backtesting frameworks

Git

Job description

Placements24 seeks a highly skilled Remote Quantitative Analyst to design and backtest trading strategies from home. You’ll leverage advanced statistics to build profitable algorithms, work with large datasets, and collaborate with portfolio managers on an algorithmic trading desk.

The ideal candidate has a strong quantitative finance background, expert programming skills in Python/C++/R, and deep knowledge of time series analysis, market microstructure, and derivatives.