<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p><strong>Who we are</strong></p><p><br/></p><p><span>WeatherPromise is a Series A startup backed by Maveron, Lerer Hippeau, and 1Sharpe among others. We guarantee good weather for travellers. If the weather doesn't deliver, customers get their money back — automatically.</span></p><p><br/></p><p><span>This isn't conceptual. We're embedded in the checkout flows of major travel partners, making real-time, destination-level decisions about weather risk for millions of customers. At the core of every decision is weather data — sourced, validated, and operationalised by our team.</span></p><p><br/></p><p><span>We're a team across Europe and the US: repeat founders, engineers, data scientists, climate scientists, and product managers from places like Meta, Klarna, HelloFresh, Snapchat, TravelPerk, and Miro, alongside researchers from leading academic institutions.</span></p><p><br/></p><p><span>---</span></p><p><br/></p><p><strong>The role</strong></p><p><br/></p><p><span>We're looking for a Climate Scientist / Data Scientist with climate experience to own the scientific exploration, evaluation, and operationalisation of our climate and weather data.</span></p><p><br/></p><p><span>This role sits at the intersection of research, data engineering, and product. You won't just analyse climate data — you'll decide which datasets we use, how we validate them, and how they feed into production systems that make high-stakes decisions about specific destinations, dates, and customer experiences.</span></p><p><br/></p><p><span>A hands-on role for someone who enjoys both scientific rigour and building real-world systems.</span></p><p><br/></p><p><span>---</span></p><p><br/></p><p><strong>What you'll do</strong></p><p><br/></p><p><span>- Scout and evaluate climate and weather datasets globally — historical, forecast, satellite, reanalysis, proprietary — and recommend what we should use and why</span></p><p><span>- Assess fitness-for-purpose: can a dataset support destination-level, time-bound decision-making at the granularity our product requires?</span></p><p><span>- Evaluate trade-offs across providers on coverage, resolution, latency, reliability, and cost</span></p><p><span>- Design validation frameworks to benchmark datasets against ground truth or alternatives</span></p><p><span>- Clean, transform, and standardise raw climate/weather data into production-ready formats</span></p><p><span>- Work with data engineering to build and maintain AWS pipelines that serve these datasets to downstream teams</span></p><p><span>- Process and analyse satellite, radar, model, and weather station data</span></p><p><span>- Develop bias-adjustment and other research applications together with the Head of Climate Science</span></p><p><span>- Collaborate with data science to enable modelling and experimentation</span></p><p><span>- Translate scientific findings into clear recommendations for product and business teams</span></p><p><br/></p><p><span>---</span></p><p><br/></p><p><strong>What you bring</strong></p><p><br/></p><p><strong>Must-haves</strong></p><p><br/></p><p><span>- Strong proficiency in Python (and potentially R) for data analysis, processing, and engineering</span></p><p><span>- Hands-on experience with geospatial weather data, including satellite, radar, model, and station data</span></p><p><span>- Familiarity with common data formats — NetCDF, GRIB, raster data, etc.</span></p><p><span>- Experience with data engineering, pipelines, API access, AWS computing</span></p><p><span>- Experience analysing data quality, bias, and uncertainty</span></p><p><span>- Experience deploying or maintaining data pipelines in production environments</span></p><p><span>- Ability to bridge the gap between scientific analysis and practical implementation</span></p><p><br/></p><p><strong>Good signs</strong></p><p><br/></p><p><span>- You've taken real-world datasets from exploration through to production use</span></p><p><span>- You're comfortable with incomplete, messy, and evolving data sources</span></p><p><span>- You can explain complex scientific concepts to non-technical teams</span></p><p><span>- You understand how data choices impact product and customer outcomes</span></p><p><span>- You're motivated by impact, not just academic publication</span></p><p><span>- You'd rather build something imperfect and iterate than wait for perfect conditions</span></p><p><span>- You're interested in working in a low-hierarchy start-up environment</span></p><p><br/></p><p><span>---</span></p><p><br/></p><p><strong>Why this role</strong></p><p><br/></p><p><span>- You'll define the scientific data backbone of a company creating a new category in travel</span></p><p><span>- Weather data here drives real-time, customer-facing decisions — not academic papers or commodity trades</span></p><p><span>- You'll have autonomy to explore, evaluate, and implement the best data sources available</span></p><p><span>- The role bridges applied research and production systems — a rare combination</span></p><p><span>- You'll shape how weather data is used in a completely new way</span></p> </div>