- Location
- Gurugram, Haryana, India · Singapore
- Type
- Internship
- Department
- Quantitative Trading
- Seniority
- Internship
- Education
- Master
- Source
- Greenhouse
Description
Quantitative Research Intern
Every trading decision begins as a research question.
At Graviton, we don't believe great trading starts with instinct.
It starts with curiosity.
Every strategy, every model and every edge begins with someone asking a better question than everyone else.
As a Quantitative Research Intern, you'll spend eight weeks working on research that directly influences how we understand markets and build trading strategies. You'll collaborate with quantitative researchers and technologists to investigate market behaviour, test hypotheses, build predictive models and solve problems where the answers aren't obvious.
This isn't an internship where you'll observe from the sidelines.
You'll own the research that matters. You'll challenge assumptions, build new ideas, validate them with data and see how rigorous research translates into real trading decisions. Outstanding work has the potential to shape production strategies and create measurable PnL impact.
If you enjoy solving difficult mathematical problems, writing elegant code and discovering patterns hidden inside complex data, you'll fit right in.
What You'll Work On
Over eight weeks you'll contribute to research across multiple areas of systematic trading.
Your work will include:
- Discovering predictive patterns from billions of market events.
- Designing statistical models that identify trading opportunities.
- Applying probability, optimization and machine learning to challenging research problems.
- Building AI-powered research agents that accelerate idea generation, experimentation and analysis.
- Developing research infrastructure that enables rapid experimentation and large-scale data analysis.
- Designing rigorous experiments and backtests to evaluate hypotheses.
- Working with traders to translate research into production-ready trading signals.
- Measuring strategy performance, identifying improvements and refining models.
- Exploring new techniques from machine learning, artificial intelligence and quantitative finance to discover the next source of alpha.
No two projects are identical. The problems change constantly and so does the way you'll think about solving them.
What You'll Learn: You'll leave with far more than another internship on your resume.
Over the eight weeks you'll gain practical experience with the techniques used by one of the world's leading quantitative trading firms.
You'll develop hands-on experience in:
- Quantitative research for live trading
- Statistical modelling and predictive analytics
- Machine learning for financial markets
- Market microstructure and electronic trading
- Large-scale data engineering and research pipelines
- Experimental design and hypothesis testing
- Backtesting and model evaluation
- AI-assisted research workflows
- Communicating complex research with clarity
Most importantly, you'll learn how experienced quantitative researchers approach difficult problems - breaking them down, questioning assumptions and making decisions using evidence rather than intuition.
Mentorship That Accelerates Growth
Every intern is paired with:
- A dedicated mentor who guides technical development.
- A reporting manager who provides continuous feedback.
- A buddy who helps you navigate the internship experience.
You'll receive regular code reviews, research discussions and feedback sessions, ensuring you grow throughout the internship - not just at the end of it.
What Success Looks Like
By the end of the internship, successful interns will have:
- Delivered a complete research project from hypothesis to evaluation.
- Built quantitative models grounded in statistical rigor.
- Presented research findings to experienced researchers and traders.
- Contributed tools, infrastructure or models that improve the research process.
- Demonstrated intellectual curiosity, ownership and the ability to solve open-ended problems.
Who We're Looking For: We're looking for exceptional students who genuinely enjoy solving hard problems.
Education
- Pursuing a Bachelor's or Integrated Master's degree
- Expected graduation in 2028
- Mathematics, Computer Science or Electrical Engineering
- CGPA of 8.5 or above
- No active backlogs
Technical Foundation
- Strong programming skills in Python and/or C++
- A solid understanding of probability, statistics, linear algebra and optimization
- Experience with machine learning, statistical modelling or data analysis through coursework, research or personal projects
- Confidence working with large datasets
- Strong analytical thinking and problem-solving ability
What We Value: More than specific technologies, we're interested in how you think.
We look for people who are:
- Curious enough to question assumptions.
- Analytical enough to separate signal from noise.
- Persistent enough to keep searching when the first answer isn't the right one.
- Humble enough to learn continuously.
- Excited by difficult problems that don't have textbook solutions.
Why Graviton?
At Graviton, you'll find an environment built around ideas.
Researchers sit alongside traders and engineers, collaborating to solve problems where milliseconds matter and better models create real competitive advantage.
You'll work with talented peers, receive meaningful ownership from day one and learn in a culture that values intellectual honesty, curiosity and continuous improvement.
Your contribution won't be measured by the hours you spend.
It will be measured by the quality of your thinking.
