Hiring: Remote Quantitative Researcher (Full-Time) | Python, Machine Learning & Systematic Trading

Olivia Ezeani
🇳🇬 GabbyWall Job Alert

Hiring: Quantitative Researcher

Are you passionate about mathematics, data, Python and financial markets? This opportunity could be worth a closer look if you enjoy turning complex data into systematic trading ideas and testing whether those ideas hold up in real-world conditions.

📍 Location Remote
💼 Employment Full-time
📊 Focus Systematic Trading, Python & ML
Quantitative Research Python Machine Learning Financial Data

If you have been looking for a role that combines analytical thinking, programming and financial research, take a moment to review the requirements below. You can also explore other opportunities on GabbyWall while preparing your application.

💡 Job seeker tip: You do not need to apply for every vacancy you see. Focus on roles that match your strongest skills, then make it easy for the recruiter to see that match in your CV.

About This Opportunity

Quantitative researchers use mathematics, statistics, programming and financial data to investigate trading strategies. Their work often involves forming a hypothesis, testing it against historical data, measuring risk and checking whether the results are robust enough to justify further research.

For this position, the listed specialisation is Systematic Trading, Python and Machine Learning. Candidates should be comfortable working with data, testing assumptions and evaluating strategies carefully rather than relying on attractive backtest results alone.

The role is listed as remote and full-time. Review the requirements below to decide whether your background is a good fit before applying.

💡 Career tip: If you have completed a relevant research project, built a backtesting tool or analysed financial datasets, consider showcasing that work in your portfolio. A clear explanation of your approach can help demonstrate your practical skills.

Requirements

The following skills and experience are listed for this opportunity. Review each requirement honestly and highlight the relevant evidence in your application.

  • Strong background in Mathematics, Statistics, Physics, Computer Science, Electrical Engineering or a related field.
  • Experience researching and backtesting systematic trading strategies.
  • Strong Python skills, including Pandas and NumPy.
  • Knowledge of statistical modelling, machine learning and risk management.
  • Experience working with large financial datasets and out-of-sample testing.
  • Ability to validate strategies while accounting for transaction costs and risk.
💡 CV tip: Do not simply write “Python proficient.” If accurate, describe what you have built or analysed with Python, which libraries you used and what the project demonstrated. Specific evidence is more useful than a long list of buzzwords.

Nice-to-Have Skills

The following experience may strengthen an application, although it is presented as desirable rather than part of the core requirements.

  • Experience working with live trading systems.
  • SQL proficiency.
  • Experience with cryptocurrency or 24/7 markets.

If you meet the core requirements but lack one of these additional skills, do not automatically rule yourself out. Assess the actual application criteria and present your relevant experience clearly.

💡 Confidence tip: Be honest about what you know and what you are still learning. A well-explained project that demonstrates strong fundamentals can be more convincing than claiming expertise you cannot support.

How to Strengthen Your Application

Before submitting your application, take a little time to make sure your CV reflects the work you can actually do. A targeted application is easier to assess than one that lists unrelated skills without showing how they connect to the role.

1. Tailor your CV to the position

Bring relevant skills such as Python, Pandas, NumPy, statistical modelling, machine learning and financial data analysis into clear view where they genuinely reflect your experience.

2. Show evidence of your work

Where available, include relevant projects, research, code samples or portfolio links. Explain the problem you investigated, your approach and the result. Never invent results or claim work you did not complete.

3. Demonstrate research discipline

For a quantitative role, be prepared to discuss how you test assumptions, avoid data leakage, evaluate out-of-sample performance and account for transaction costs and risk.

4. Review before submitting

Check spelling, dates, contact details and portfolio links. Make sure the most relevant information is easy to find, especially on a mobile screen.

💡 Small step, real progress: You do not need to rebuild your entire CV today. Start by improving the summary and most relevant project descriptions for this role. Consistent, thoughtful applications can make your job search more manageable.
Important Disclaimer

GabbyWall does not employ candidates or directly give out jobs. We share job opportunities from available sources to make them easier for job seekers to discover.

Your next step starts here

Ready to Apply for the Quantitative Researcher Role?

If your background matches the requirements and you are ready to take the next step, use the application link below to submit your application.

Apply Now ↗ Review your details and CV before submitting.

Good luck with your application. Keep learning, keep building and keep looking for opportunities that match your strengths.

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