Are you a finance or business student who wants to understand how revenue works inside a fast-scaling technology company — not just in theory, but in practice?

The Global Revenue Assurance group within Finance Operations owns the order-to-cash cycle — and our remit starts earlier than most, from the moment a deal is structured to the moment it appears correctly in financial statements. We operate across multiple entities, currencies, and contract structures, connecting two million machines in the construction industry to the numbers that account for them. Our job is to make sure those numbers tell the truth, and to change the processes that make them lie.

Trackunit has grown from 150 to 450 people since 2020. The problems we work on have grown with us — and so have opportunities for the people inside the function.

What you'll work on

From how a deal is structured in Salesforce, through how it's set up in our billing systems, to how it appears in the financial statements — you'll work across the full order-to-cash cycle. That means finding gaps with commercial consequence: a pricing setup that doesn't reflect what was sold, a product bundle where recognition timing was applied inconsistently, a process that worked at one scale and silently stopped working at another. You'll support period-end close, contribute to leakage analysis, form a view on root cause, and translate findings into something a non-finance audience can act on. Your work feeds directly into process improvements, not just the analysis that precedes them.

What you'll gain

You'll join a small, senior team — close enough that your work is visible from day one, structured enough that you'll have real guidance when you need it. The exposure is genuine: live problems, real financial consequence, direct access to the Global Revenue Assurance Manager. You'll build analytical habits that transfer anywhere, learn to communicate financial insight across functions, and learn how to apply AI to real analytical work. You'll use the tools the industry uses — Salesforce, NetSuite, Databricks, Power BI, and Claude — and leave knowing how to apply them to real analytical problems. That combination of domain knowledge, rigour, and AI-augmented practice is what this team runs on — and what you'll carry with you.

Practicalities

Location: Copenhagen, hybrid setup. We'd love to have you in the office where it works alongside your studies. Time commitment is 15–20 hours per week, structured around your academic calendar including exam periods. We're looking for students mid-way through a bachelor's or early in a master's.

Who you are

You're the kind of person who, when given an answer, wonders whether the right question was asked. When something feels off, you follow the thread — you don't rationalise it. You've probably always been this way: the one who asks the second question, who notices the assumption buried in the argument.

You have a bias toward resolution. Finding the gap is the beginning, not the output. You stay with a problem until the root cause is confirmed, the implication is understood, and something has changed. Incomplete work makes you uncomfortable — not anxious, just unwilling to stop there.

And you know how to bring people with you. You can take something technically precise and explain what it means to someone with a different frame — without losing the nuance. In a team that spans Finance, Commercial, and Operations, that's how insight becomes action.

We can teach tools. We're looking for people who know how to think, finish what they start, and move an organisation forward.

What you bring

• Currently studying toward a bachelor's or master's degree. A background in business, economics, finance, law, or a related field is a natural fit — but if you're studying something different and have built relevant experience in finance or analytical work, we're interested in that too.

• Comfortable in Excel and curious about how systems and data connect to financial outcomes.

• Experience with any of the following — Power BI, Salesforce, NetSuite, or Databricks — is a plus.

• Comfort with AI tools — we use Claude day-to-day — is an advantage, though not a condition.

• You've done something — a project, a role, a piece of work — where you identified a problem nobody asked you to find and did something about it.

• English is your working language, written and spoken.

Our hiring process

No cover letter. We want to see how you think, not how you write introductions.

1. Intro call — 30 minutes. A chance to get to know each other. We'll tell you about the team, the function, and what the work looks like day-to-day. You tell us about yourself and what you're looking for. No preparation needed — just a conversation.

2. Scenario interview — we'll share a few situations in advance drawn from the kind of work this role involves. We'll talk through how you'd approach them together. There's no single right answer — we're interested in how you think, what you notice, and how you communicate what you find.

3. Offer and start date.