Quantitative Researcher (2027 Graduate)

Quantitative Researcher

Every trading strategy begins with a question worth answering.

At Graviton, we believe the best trading strategies don't come from following established playbooks.

They come from asking better questions.

Why does a pattern exist?
What is driving it?
Is it real or just noise?
Can it be explained, modelled and turned into an edge?

As a Quantitative Researcher, you'll work on these questions every day.

You'll investigate market behaviour, develop quantitative models, build and test hypotheses and turn insights into trading strategies. You'll work alongside quantitative researchers and technologists in an environment where research moves quickly from an idea on a whiteboard to something that can influence live trading.

The problems are open-ended. The data is enormous. The answers aren't in a textbook.

You'll be expected to find them.

What You'll Work On

You'll work across different areas of quantitative research and systematic trading. Depending on your team and research interests, your work may include:

• Discovering predictive patterns and sources of alpha from billions of market events.
• Formulating hypotheses about market behaviour and designing experiments to test them.
• Applying probability, statistics, optimization and machine learning to complex research problems.
• Building predictive models and quantitative signals for systematic trading.
• Developing and improving research infrastructure that enables faster experimentation and deeper analysis.
• Working with large and complex datasets to uncover patterns that aren't immediately visible.
• Designing robust backtests and statistical tests to distinguish genuine signals from noise.
• Investigating market microstructure and understanding how markets behave at different timescales.
• Evaluating strategy performance, identifying weaknesses and continuously refining models.
• Working closely with technologists to translate research ideas into efficient, production-ready systems.
• Building AI-powered research tools and agents that accelerate idea generation, experimentation and analysis.
• Exploring new techniques in machine learning, artificial intelligence, statistics and quantitative finance to uncover new sources of edge.

No two research problems are the same.

The questions change. The data changes. The assumptions change.

That's what makes the work interesting.

The Research Challenge

Quantitative research isn't about finding an answer.

It's about finding an answer you can trust.

You'll constantly ask:

• Is this signal real or statistical noise?
• Why does this pattern exist?
• What assumptions are we making?
• How robust is the result?
• What happens when the market changes?
• Can we explain the behaviour we're seeing?
• How do we turn an interesting observation into a repeatable trading strategy?

You'll work through these questions using data, mathematics, experimentation and rigorous reasoning.

Good research finds patterns. Great research understands why they exist.

From Hypothesis to Impact

At Graviton, research doesn't end with a model that looks good in a backtest.

You'll have the opportunity to take ideas through the entire research lifecycle:

Question → Hypothesis → Experiment → Model → Validation → Strategy → Production

You'll work with researchers and technologists to understand how an idea behaves in real markets and how it can be translated into a robust trading system.

The strongest ideas can move all the way from research to live trading and measurable PnL impact.

Ownership From Day One

Graviton operates on the belief that great research comes from giving great researchers room to think.

You'll have meaningful ownership over research problems while working closely with experienced researchers and technologists.

You'll be expected to:

• Form your own hypotheses.
• Challenge existing approaches.
• Design rigorous experiments.
• Decide what is worth investigating.
• Follow evidence wherever it leads.
• Know when an idea isn't working and move on.
• Communicate your thinking clearly.
• Turn promising research into something others can build on.

There is no prescribed formula for finding alpha.

Your job is to discover one.

What Success Looks Like

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