Thermosphr
Data Analyst | Climate Tech Startup
Skills
16 days ago
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Important information
Contract type:
Permanent
Location:
Paris, France
Work mode:
Onsite
Published on:
5 October 2026
What they need
We do not simply analyse buildings; we pilot them using data - a single error can affect twenty buildings at once, and a single fix can scale just as fast.
Reporting to the Data & Product Lead, and working closely with the Operations and Tech teams, you will own two priorities. First, operational performance: identifying where piloting deviates across the portfolio, tracing it back to the underlying data or control-logic issue, and correcting it with the accuracy the scale demands. Second, the speed and reliability of the team’s work: understanding what colleagues actually need, building the tooling that removes manual work, and ensuring it is genuinely adopted, not simply delivered.
We move fast, ship solutions that work at roughly 80%, and improve them from there. The scope will evolve quickly, and whoever takes this on early will grow with it.
Responsibilities include:
Own real-time visibility across approximately 500 pieces of equipment, built independently or with IT: establishing how equipment failures are detected, and whether they can be flagged or resolved automatically before they cost a week of data or energy.
Identify underperformance before it becomes costly: when a building’s savings fall below, or never reach, break-even, trace the issue to its root cause and raise the alert.
Own energy savings estimates end-to-end: forecast a building’s achievable savings prior to sale, then continuously refine the model against actual equipment types, building characteristics, and outcomes until it is accurate.
Spot inefficiencies in how the team works, quantify their cost (time, money, or energy), design an MVP fix prototyped with AI within days, then build the long-term solution with the Tech team for proper delivery within weeks rather than quarters. Quantify the gain once it ships, and make sure it’s actually adopted by users.Preferred experience
We are looking for a high-potential profile, with 2-4 years of experience in a demanding, fast-moving environment - whether in data, analytics, operations, or a technical role within a high-growth company.
More important than a specific background, we are looking for:
Hands-on experience across a range of data and data-visualisation tools (e.g. SQL, Python, BigQuery, Metabase, Looker, Power BI), with evidence of having shipped real solutions, not merely coursework.
A proven track record: a tool you designed or built that achieved measurable impact (adoption, time saved, or issues avoided) - ideally through AI-driven automation of real work, not just coursework or side projects
Proven experience coordinating across teams (Tech, Operations, or equivalent) to ensure a fix or tool is fully delivered, not merely proposed.
Native or bilingual proficiency in English and French
Mindset
- Technically curious - you enjoy building things from scratch and turning messy data into something people can act on.
- You ship, you iterate, and you do not wait for the perfect brief.
- Ops-curious - you care as much about why a building underperforms as about the tool you build to fix it.- 3 interviews
- 1 case study
- 1 team meeting in Paris
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