About us

Climate Policy Radar is a non-profit organisation building open databases and research tools so people can discover and understand complex information, in particular long-text documents, on climate, nature and development. Our data and tools help governments, researchers, international organisations, civil society, and the private sector to understand and advance effective climate policies and deploy climate finance. Harnessing data science and AI, and pioneering the application of natural language processing to this domain, our work renders previously unstructured, siloed data more readable and accessible.

We are a team of ~30 technologists and climate policy experts who care a lot about the 'how' (our values and culture) as well as the 'what'. As part of that, we have embraced a flexible, hybrid approach to work, including a 4 day workweek.

We are looking for a Software Engineer to join our data science team.

Roles and responsibilities

This is a growth hire, adding a software engineer to Climate Policy Radar’s data science team. Reporting to the Head of Data Science, you’ll be a fully integrated member of our team. You’re the person who will turn a promising prototype into something real - deploying models, automating pipelines, and building the infrastructure that connects us to other engineering teams.

You’ll pair frequently with data scientists to understand their needs, and work across API development, cloud infrastructure, front-end demos, and automation. A lot of the team’s best ideas are currently bottlenecked by our engineering capacity; this role exists to unlock them.

About the data science team

Climate Policy Radar’s engineering org is split into a few functional teams: programmes (domain experts), platform (high-quality data sharing), application (user-facing tools), and data science (models and evaluation). Despite those splits, most of our work is cross-functional.

The data science team builds the models that power our search engine, classifiers, and LLM workflows, and the evaluation frameworks that keep them honest. Our work directly informs policy decisions, so we care a lot about evaluation, monitoring, and minimising bias. We’re research-informed but production-focused, and we default to working in the open by publishing datasets, models, and papers wherever we can. We also share what we’ve learned through blogs, papers, and public talks.

Tech preferences

The vast majority of the data science team’s work is written in Python, so we’ll expect you to be a fluent reader/writer!

In addition, here’s an (unordered) list of tools which we work with regularly. We’re always open to new suggestions of tools you’ve had success with, but familiarity with these tools will help you integrate with our existing stack:

ML & NLP: PyTorch, Huggingface Transformers, Pydantic AI, Pandas, Spacy
APIs & backend: Python, FastAPI, Pydantic
Data & infrastructure: DuckDB, Snowflake, PostgreSQL, Docker, AWS (ECS, S3, etc.), Pulumi, Prefect, GitHub Actions
Search: Vespa
Testing, evaluation & monitoring: Pytest, Hypothesis, Weights & Biases, Posthog
Development tools: GitHub, Cursor, Claude Code

What will you be working on?

Climate Policy Radar’s core product is a search engine for 30,000+ climate policy documents, powered by ML models and classifiers developed by our data science team. The team has three major strands of work planned for 2026:

Working on our search engine to improving information retrieval
Working on classifiers to create more connections between our core data
Building workflows with LLMs which are able to synthesise disconnected pieces of evidence into a coherent answer

Your engineering expertise will unlock progress across all three strands. Over the next year, you’re likely to:

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