Who we are

Optiver is a tech-driven trading firm and leading global market maker. As one of the oldest market making institutions, we are a trusted partner of 70+ exchanges across the globe. Our mission is to constantly improve the market by injecting liquidity, providing accurate pricing, increasing transparency and acting as a stabilising force no matter the market conditions.

Our Amsterdam office is where it all began. Since our founding in 1986, Optiver’s Amsterdam office has developed into one of the most dynamic trading floors in Europe, where teams trade a wide range of products from listed derivatives to cash equities, ETFs, bonds and foreign exchange.

About the team

The Global Market Data (GMD) team is responsible for the data that underpins Optiver’s trading: exchange feeds, reference data, corporate actions, vendor analytics, and the contracts and metadata that sit behind them. We work directly with traders, quants, and engineers to make sure the right data is available, accurate, and well understood — and we are increasingly using AI to scale how we operate.

About the role

We are hiring two working students in Amsterdam to join GMD for 12 months. You will work on real operational problems alongside the team, applying AI tooling to scale how we manage market data and contributing directly to projects the trading floor relies on.

What you’ll do

Your work will span three areas. All of them make active use of the team’s AI tooling, and all of them produce output that goes into production.

Run and improve AI-driven market data operations

Take ownership of day-to-day operational workflows — contract renewals, entitlements, dataset onboardings — and make them faster and more reliable using the team’s AI tooling. Identify the next workflow worth automating and help build it.

Operationalise vendor and exchange notifications

Vendors and exchanges send a constant stream of notifications: feed migrations, format changes, fee updates, regulatory items. You’ll help build out the process that captures, classifies, and routes them — with AI doing the first pass and you ensuring the right things get to the right people.

Build the team’s data knowledge base

A modern data function depends on rich, accurate metadata: who owns what, where it comes from, how it’s shaped, who’s using it. You’ll use AI to draft and structure this information at scale, work with vendors to close information gaps, and validate the output before it lands in the systems traders rely on.

What you’ll gain

• Hands-on experience applying AI in production — prompting, validation, agentic workflows, human-in-the-loop review, and a clear sense of where LLMs add value and where they don’t

• Direct exposure to a top-tier trading firm — you’ll sit alongside traders, quants, and engineers and see how a trading business actually operates

• Concrete output you can point to — improved processes, structured datasets, and AI-driven workflows that remain in use after you leave

• A grounding in the market data industry — exchanges, vendors, contracts, licensing, and how data drives decision-making in financial markets

Who you are

• Currently studying Finance, Economics, or a related field, with a technical streak — you are comfortable scripting and willing to learn new tools quickly

• Familiar with AI tools (LLM-based assistants, agents) through study or personal projects, and curious about how to use them well

• Strong attention to detail and able to work independently on structured tasks

• Clear written and verbal communication in English

• Genuinely interested in the intersection of markets, data, and AI

Prior finance experience and a computer science background are not required. We value curiosity and a willingness to go deep on the domain.

What you’ll get

• The chance to work alongside best-in-class professionals from over 40 different countries

• Competitive working student compensation

• Daily breakfast and lunch, fully paid commuting expenses, and weekly in-house chair massages

• Training, mentorship and personal development opportunities

• Regular social events, clubs and Friday afternoon drinks

Practical details

• Hours: approximately 16–24 hours per week, flexible around your study schedule

• Location: Amsterdam office, in-person

• Duration: 12 months

• Start date: as soon as possible; applications reviewed on a rolling basis