Trading Support Analyst in Amsterdam

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.

At Graviton, we don't believe the best trading strategies 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 those questions every day. You'll investigate market behaviour, develop quantitative models, build and test hypotheses and turn insights into trading strategies, working alongside researchers and technologists in an environment where an idea on a whiteboard can reach live trading quickly. This isn't a role where the answers are in a textbook. The problems are open-ended, the data is enormous, and finding the answers is the job. Ideal candidates are rigorous thinkers who genuinely enjoy mathematics, programming and figuring out things that aren't obvious, based in our Singapore, London, Amsterdam or US offices. What You'll Work On You'll work across quantitative research and systematic trading, taking ideas through the full lifecycle: question, hypothesis, experiment, model, validation, strategy, production. Depending on your team and research interests, your work would 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 build predictive models and quantitative signals for systematic trading Designing robust backtests and statistical tests to distinguish genuine signals from noise Working with large and complex datasets to uncover patterns that aren't immediately visible Investigating market microstructure and how markets behave at different timescales Evaluating strategy performance, identifying weaknesses and continuously refining models Developing research infrastructure and AI-powered tools and agents that make experimentation faster and analysis deeper Working c

About BlockTech BlockTech is a fast-paced algorithmic trading firm. Specializing in crypto options, we facilitate global cryptocurrency derivatives and spot trading, while expanding into new markets. As we continue to grow rapidly, we are looking for a Senior Software Engineer to take technical ownership of the data infrastructure our trading and technology teams are built on. Every decision at BlockTech starts with data: exchange feeds, our own trade and account events, and the history we query to make sense of both. The Foundation team owns the systems that move, aggregate, and store all of it. We run our own Kafka, NATS, PostgreSQL, ClickHouse, and Iceberg, self-hosted and tuned by us. We work primarily in Rust, with Python and SQL alongside. This is a role for an engineer who has already built and operated data infrastructure at scale, and who wants their technical decisions to set direction rather than follow it. What will you do? You will own the pipelines and stores every other team depends on. When a researcher backtests a strategy, when a trader checks a position, when risk queries yesterday, they are all reading data your systems ingested, routed, and kept correct. As a senior engineer, you will also set the technical standards the rest of the team builds against. You will: Own the ingest path. Collect public and private exchange information and internal trading data with minimal latency impact, and land it in our trading systems in real time. Architect the streaming layer. Design and operate our Kafka and NATS messaging systems for the throughput and delivery guarantees our critical flows depend on. Build the storage layer. Develop real-time aggregation and long-term storage across PostgreSQL, ClickHouse, and Iceberg, and make the structural calls that keep queries fast as volumes grow. Run what you build. Own capacity, retention, schema evolution, and failure behavior for infrastructure we host ourselves, with no managed service to hide behind. Make the

About BlockTech BlockTech is a fast-paced algorithmic market maker facilitating global derivatives and spot trading, originating from crypto markets and expanding into new markets. We trade our own capital on systems that run 24/7 and have to be fast and correct without exception. Our systems run on Linux and are written in Rust and Python. For the Summer of 2027, we're looking for Software Engineer Interns to join our engineering team in Amsterdam. The role This is an 8-10 week summer internship at our Amsterdam office, giving you a unique opportunity to work on an end-to-end project with a real and direct business impact. You’ll work in a small team and get the chance to understand how a trading firm actually works from the inside. You will Participate in a customized training program that will give you an understanding of financial markets in general, the company and the project. Own a project from design to deployment guided by experienced software engineers. Work with production-level data and systems Learn from the best, all while leveraging cutting-edge technology What we're looking for Currently in your (pen)ultimate year studying computer science or a related discipline at a top university in Europe Available full-time in Amsterdam, for a duration of 8 - 10 weeks over the summer of 2027, starting with 5th of July Proficiency in a systems language (ideally Rust and/orC++) and working knowledge of Python A solid grasp of data structures, algorithms, and what actually makes code fast A critical mind that follows things until completion, high ownership, and clear communication in English What's in it for you? A summer internship in a relaxed and modern office in Amsterdam A dedicated mentor, a team of fellow interns and full-time software engineers, an in-house training program, and exposure to how engineering, research, and trading actually work together The opportunity to work at the forefront of automated trading using state-of-the-art technology, in an envi