Talent Acquisition Associate (Contract)
nplan
| Company | nplan |
| Category | Uncategorised |
| Location | — |
| Remote | — |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 28 Jul 2026 |
| Last verified | 2 Aug 2026 |
| Source | Employer ATS (teamtailor) |
Description
Talent Acquisition Associate (Contractor) People · London · Hybrid Accelerate the growth of our team — hiring the people who forecast risk on HS2, Heathrow and Sizewell C. If you're early in your career and want a job that’s aligned with your exceptional achievements, not your tenure, join nPlan… Own the whole thing. Five to seven live searches, brief to accepted offer. No coordinator beneath you, nobody above you doing the interesting parts. We're a company of around fifty people, so one hire visibly moves it. Hunt for people who don't answer job ads. ML researchers, product people who can hold their own with programme directors, enterprise sellers who sell into infrastructure. Small pools, no inbound shortcut. This is most of the job. Work like a talent team of five, as one person. We’re an AI company, so obviously we know what AI can do. We'll give you the AI tooling and the time to learn it properly. What we need is someone who'll actually run with it. We’re looking for the person who’s blowing the roof off the expectations of what good looks like at your level and wants to take real ownership and accelerate their growth. This is a contractor role that has the potential to grow into more. nPlan is growing fast and we’re always on the lookout for exceptional talent that can help us create a step-change in the growth of our business. Ready to reshape one of the world's largest industries? nPlan has built a unique AI platform that turns the data behind major construction projects into decisions their leaders can act on — forecasting delay and cost risk on some of the world's most important infrastructure, and helping the people running those projects decide what to do about it. Behind that is a machine learning capability that forecasts project risk more accurately than anything else on the market, trained on one of the largest datasets of construction schedules in existence, and built by a world-class engineering and research team recognised as a MacRobert Prize finalist, the UK's top engineering award. Every hire you make goes into that team. The role — please make sure this excites and energizes you We don't have a talent team. We have this role, and the hiring managers you'll partner with. That's a wider remit than someone a few years in usually gets. That’s because we'd rather back one person who is hungry and learning fast, with real ownership and real support, than hire someone senior to do a fraction of what they're capable of. The bet only works if you close the gap quickly, so we've been specific below about where we'll carry you and where we won't. One important thing: If you’re not comfortable picking up the phone, please don’t apply. You’ll have three main focus areas: Sourcing is the engine, not the fallback. We hire for competencies that are genuinely scarce, and passive channels don't fill those roles. You'll run active, targeted outbound as the default, with the structure to keep five to seven searches alive at once without any of them going quiet for a fortnight. This is the part we expect you to already be good at. We want recruiting here to be data-driven. We've started building the infrastructure, and now need you to use it and help us improve it.You will be asked to keep the data honest, know your own numbers cold, and change what you're doing when they tell you to. We'd rather you kill a sourcing channel with evidence and move on to the next one than defend one with anecdote. AI is how one person covers this much ground. We’re an AI company, so obviously we know what AI can do. We don't expect you to arrive with a built-out AI workflow but we do expect someone who teaches themselves quickly and is truly curious. You'll get proper onboarding on the tooling, a budget for more, and roughly