Build the ingestion layer that reads BMS points, meters and IoT devices across a growing portfolio, and make that data trustworthy enough to underwrite against.
neos runs an optimisation layer on top of building plant that already exists. Everything downstream of that — the control decisions, the savings evidence, the CRREM tracking — depends on the quality of the data we read.
What you would work on
Connectors for BMS protocols, meter data and IoT devices, across buildings that were never designed to be read from. Validation and gap-filling for consumption data that arrives late, in the wrong units, or not at all. The normalised baseline model that every savings claim we publish is measured against.
What we look for
Strong data engineering fundamentals and a tolerance for messy industrial data. Direct experience with building systems, metering or energy markets is useful but not required — we can teach the domain.
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