Company / Careers / Engineering
Data Analyst
You put our firmographic data to work in client-facing prototypes: dig into its quality, shape it to fit a prospect's real needs, and turn it into the proof that wins a POC. Plenty of technical work, with the business context always in view.
Full disclosure
The way we work is not for everyone, and that's fine. We'd rather you know now than three interviews in. We dislike every side of micromanagement, so no one will hand you a detailed plan. You'll own things before you feel ready and the pace doesn't ease up.
If this sounds frustrating, trust that feeling. If it sounds like your kind of place, let's talk.
Who we are
- A deeptech startup of 60 people in Bucharest, building the machine that reads the company world.
- Our customers include the giants of the data world, the same companies you'd expect to be our competitors.
- Founded in 2019, VC-backed. The team stays small on purpose, so decisions stay with the person doing the work.
- Most of the team is technical, founders included. The decisions that shape the company are made by people who understand the low-level work behind it.
- What we run in-house (from our crawlers to our own LLMs) is what several entire companies get built around. Here it's only one team.
Who you are
- You own your work like a founder owns a product.
- A growth mindset, able to capitalize on unprecedented contexts through your skills and abilities.
- A strong problem solver, visible in the way you deal with the tension between brief and shipping.
- Resilient, especially in front of failure, the kind that always comes paired with pioneering work.
- An appetite to grapple with a variety of technical challenges.
What we do
- Crawl the entire internet and decide, page by page, what matters.
- Interpret everything we find with LLMs we train ourselves, in 125 languages.
- Resolve every source under the company it belongs to, in one living graph of 135M+ companies.
- Trace every datapoint back to the source it came from, so every judgment can be defended.
- Keep the history, so we notice when any one of them changes.
What you'll do
- Analyze data quality knowing the outliers you catch and the KPIs you define are what decide how good our data really is when a buyer puts it to the test.
- Understand the business context behind every use case and make the data answer it, acting as the translation layer between what the graph knows and what the buyer needs.
- Shape, fine-tune, and quickly prototype data assets around each prospect's real case, because PoCs are where deals are won or lost and the proof is yours to build.
- Research and validate new web sources, as what you confirm becomes part of what our graph knows about millions of companies.
- Curate and test the training datasets the Machine Learning team builds on, so your judgment about what's right gets baked into the models themselves.
What you'll find here
- Founders who built products serving billions of users, across web, big data, and cloud.
- Infrastructure most companies rent, built and run in-house: crawlers, GPUs, custom LLMs.
- Scale you'd otherwise wait a career to touch: 4.2B pages a month, 3M tokens a second, from day one.
- Problems no one has solved before, some so far out that academic papers are the only formal guide we have.
- Five disciplines under one roof (crawling, ML, big data, infrastructure, product) close enough that you see how all of them actually work.
What we look for
- The habit of investigating the data before trusting it.
- Strong Excel and solid SQL are a must, Apache Spark, Scala or Python are a plus.
- The instinct to frame the problem before touching the data.
- Judgment on trade-offs you can defend out loud: what to build properly, what to approximate, and why.
- The ability to connect data to what a business actually needs, and to say what you found in plain language, both to the team, and when it counts, to the client.
What we offer
- Fair, market-aligned base, ESOP tied to impact (for permanent roles), and a high salary growth rate tied to performance.
- Decisions that would need three approvals elsewhere are yours to make, and yours to answer for.
- Growth at the pace you can take, and responsibility that expands as fast as you prove you can hold it.
- What you build lands in front of some of the largest companies in the world, often within weeks.
- Steep learning curve, no matter how experienced you are, with people who've climbed it a desk away when you're stuck.
What we expect in return
- High tolerance for ambiguity, marked by your ambition to push forward with incomplete information.
- High speed and uncompromising quality in your work.
- The ability to quickly and effectively evaluate technical tradeoffs and translate them into relevant scenarios
- Genuine aversion to any customer or colleague struggling with something you delivered.
- Ask what would make it ten times better, starting with your own work.
How we hire
A process built to help both of us decide.
We keep it informal because that's how we actually work. And we take it seriously because one hire can change a company this size. The way we communicate throughout is designed so that either of us can openly say it isn't working, even mid-interview.
- 1Home AssignmentA hands-on problem cut from the real work of this role. You'll know what the job is like before you say yes to it, and so will we.
- 2Team interviewsSessions with the people you would actually work beside, one of which is face-to-face and includes live tasks.
- 3DecisionA yes or a no, typically fast. We do not ghost.
Careers
Recognize yourself in all of this?
Send your application and a note on why this role fits. We read every one, and if it matches what we're looking for, you'll hear from us.
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