Quantitative Researcher PhD - 2027 Internship

Posted 8 Days Ago
Be an Early Applicant
3 Locations
In-Office
Internship
Financial Services
The Role
Conduct quantitative research on financial markets by discovering predictive patterns, developing statistical and machine learning models, running large-scale simulations and backtests, and translating research into production-ready trading signals. Interns collaborate with researchers and technologists, build research infrastructure and AI-powered agents, and complete rigorous projects from hypothesis through evaluation under realistic market conditions.
Summary Generated by Built In

At Graviton, every strategy, model and edge begins not with instinct, but with someone asking a better question than everyone else.

As a PhD Quantitative Research Intern, you'll spend 10-12 weeks pointing the research skills you've spent years building at markets. You'll collaborate with 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 observe from the sidelines, or re-run someone else's experiment. Outstanding work has the potential to shape production strategies and generate real, measurable returns.

Ideal candidates are researchers who want to see their methods meet live markets: mathematicians, physicists, statisticians and computer scientists who are excited to solve the hardest problems in our field, across our offices in the US, Singapore, Amsterdam and London.

What You'll Work On
You'll work on real research problems, not simulated exercises. Your work would include:

  • Discovering predictive patterns from billions of market events
  • Designing statistical models that identify trading opportunities
  • Applying probability, optimization and machine learning to open research problems
  • Running large-scale simulations and experiments on high-performance research infrastructure
  • Designing experiments and backtests to evaluate hypotheses
  • Building AI-powered research agents that accelerate experimentation
  • Developing infrastructure for rapid, large-scale research
  • Translating research into production-ready trading signals
  • Exploring new ML, AI and quant finance techniques to find the next source of alpha

What You'll Learn
Beyond the technical exposure, you'll learn what changes when research meets live markets: why a result that would survive peer review can still fail as a trading signal, how costs and capacity constrain an idea that looks clean on paper, and how to tell a model that is right from one that is right for the wrong reason. You'll be paired with a mentor, reporting manager and buddy, with regular code reviews and feedback throughout the internship.

What Success Looks Like
Successful interns leave having delivered a complete research project from hypothesis through to evaluation under realistic market conditions, built statistically rigorous models, and demonstrated curiosity, ownership and the ability to solve open-ended problems.

Who We're Looking For
We're looking for exceptional researchers who genuinely enjoy solving hard problems.

  • Full-time PhD student in a quantitative discipline such as mathematics, physics, computer science, statistics or a related field, graduating 2028
  • Strong programming skills in Python and/or C++
  • Depth in probability, statistics, linear algebra and optimization, with research experience in machine learning, statistical modelling or data analysis
  • Comfort working with large, complex datasets, and strong analytical thinking
  • A passion for applying quantitative thinking and rigorous research to solve open-ended problems in markets
  • Strong communication skills, with the ability to explain complex ideas clearly

Our Culture
More than specific technologies, we care 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 past the first answer, humble enough to keep learning, and excited by problems without textbook solutions.

At Graviton, researchers sit alongside engineers to solve problems where milliseconds matter and better models create real competitive advantage. You'll get meaningful ownership from day one, in a culture built on intellectual honesty and continuous improvement. Your contribution won't be measured by hours spent, but by the quality of your thinking.

Markets are among the most complex systems humans have ever created. Every day, someone discovers a better answer. This summer, that someone could be you.

Skills Required

  • Full-time PhD student in mathematics, physics, computer science, statistics, or a related quantitative discipline, graduating in 2028
  • Strong programming skills in Python and/or C++
  • Strong knowledge of probability, statistics, linear algebra, and optimization
  • Research experience in machine learning, statistical modeling, or data analysis
  • Ability to work with large, complex datasets
  • Strong analytical thinking
  • Passion for applying quantitative thinking and rigorous research to open-ended market problems
  • Strong communication skills and ability to explain complex ideas clearly
Am I A Good Fit?
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The Company
HQ: Gurugram
225 Employees
Year Founded: 2014

What We Do

Graviton is a quantitative investment firm established in 2014. Since our inception, we have created a team of researchers, portfolio managers, and technologists. The use of quantitative analysis and insights in financial markets enables us to compete in some of the most complex and competitive products. As an emerging electronic trading firm, we integrate disciplines such as computer science, finance, systems engineering, and statistics. We have a team of passionate engineers and traders who have built some of the fastest systems for trading. Graviton has some of the most accomplished quantitative traders in India. We have separate trading teams who use a wide range of trading strategies across different asset classes. Each of our trading teams maintains a focus on their individual processes while being supported from the core support team. Our trading teams have strategic autonomy but have access to resources which are shared across the organization like software, technology, and connectivity. They also exchange market data and memberships, compliance and all related support functions which are needed to handle the business process with precision.

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