Climate Scientist

Who we are

Weather Promise 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.

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.

We're a team across Europe and the US: repeat founders, engineers, data scientists, climate scientists, and product managers from places like Meta, Klarna, Hello Fresh, Snapchat, Travel Perk, and Miro, alongside researchers from leading academic institutions.

---

The role

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.

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.

A hands-on role for someone who enjoys both scientific rigour and building real-world systems.

---

What you'll do

• Scout and evaluate climate and weather datasets globally — historical, forecast, satellite, reanalysis, proprietary — and recommend what we should use and why
• Assess fitness-for-purpose: can a dataset support destination-level, time-bound decision-making at the granularity our product requires?
• Evaluate trade-offs across providers on coverage, resolution, latency, reliability, and cost
• Design validation frameworks to benchmark datasets against ground truth or alternatives
• Clean, transform, and standardise raw climate/weather data into production-ready formats
• Work with data engineering to build and maintain AWS pipelines that serve these datasets to downstream teams
• Process and analyse satellite, radar, model, and weather station data
• Develop bias-adjustment and other research applications together with the Head of Climate Science
• Collaborate with data science to enable modelling and experimentation
• Translate scientific findings into clear recommendations for product and business teams
• ---

What you bring

• Must-haves
• Strong proficiency in Python (and potentially R) for data analysis, processing, and engineering
• Hands-on experience with geospatial weather data, including satellite, radar, model, and station data
• Familiarity with common data formats — Net CDF, GRIB, raster data, etc.
• Experience with data engineering, pipelines, API access, AWS computing
• Experience analysing data quality, bias, and uncertainty
• Experience deploying or maintaining data pipelines in production environments
• Ability to bridge the gap between scientific analysis and practical implementation
• Good signs
• You've taken real-world datasets from exploration through to production use
• You're comfortable with incomplete, messy, and evolving data sources
• You can explain complex scientific concepts to non-technical teams
• You understand how data choices impact product and customer outcomes
• You're motivated by impact, not just academic publication
• You'd rather build something imperfect and iterate than wait for perfect conditions
• You're interested in working in a low-hierarchy start-up environment
• ---
• Why this role
• You'll define the scientific data backbone of a company creating a new category in travel
• Weather data here drives real-time, customer-facing decisions — not academic papers or commodity trades
• You'll have autonomy to explore, evaluate, and implement the best data sources available
• The role bridges applied research and production systems — a rare combination
• You'll shape how weather data is used in a completely new way