• The company ran a defined Data Science Graduate Scheme (12 months) with four three-month rotations across teams, which is a strong, explicit early-career entry door when active.
• Peak has advertised internship routes (including long-term STEM placements), but current “open positions” listed on Peak’s site mainly point to experienced commercial and specialist roles via UiPath.
• The company does not currently show multiple always-on 0–3 year full-time roles on the public-facing roles list, which weakens evidence of repeat junior intake today.

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• The company describes a staged process publicly (intro call, team meeting, a task you present back, then leadership chat), which helps early-career candidates plan effort.
• Peak has candidate interview feedback indicating multi-round technical processes with clear stages, but that consistency varies by role and team.
• The company has public complaints about communication and experience quality in some reviews, which keeps fairness below the top band.

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• The company has described a two-week induction plus a technical “Basecamp” training track for new data scientists, which is exactly the kind of ramp structure juniors benefit from.
• Peak’s graduate scheme design used rotations and a shared group project, which creates hands-on learning rather than narrow single-team exposure.
• The company does not publish a consistent, role-by-role onboarding plan (buddying, 1:1 cadence, review checkpoints) for the broader org, so support signals cluster around data science more than every function.

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• The company has compensation-and-benefits signals in third-party reporting, but Peak rarely publishes salary ranges in role ads that early-career candidates can reliably access.
• Peak’s current roles are often posted through UiPath’s systems, and compensation visibility depends on location and posting channel rather than being consistently stated up front.
• The company has limited public, specific benefits detail tied to early-career roles, which caps confidence on pay fairness and stability for grads.

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• The company has published at least one early-career story from a Data Science Graduate explaining why they joined and what they learned, which supports the idea that some juniors ramp well.
• Peak has public reporting and employee reviews that reference layoffs and turmoil during the pre-acquisition period, which is negative evidence for early-career stability.
• The company does not publish measurable outcomes such as internship-to-offer conversion, time-to-promotion, or 12–24 month retention for early-career hires, so outcomes stay hard-capped.

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