About the companyOur client is an award-winning climate risk analytics software company who have built a SaaS platform that helps global corporates and financial institutions measure the financial impact of climate and nature-related risks. It covers physical, transition and nature risk, along with scenario modelling, stress testing and decarbonisation planning. The platform is used by multinational brands, banks, private equity firms and asset managers.

The roleThey are looking for a mid-to-senior Software Developer to join the engineering team. You will help build and scale the platform that delivers the research team’s models to clients. That means turning complex climate and financial analytics into fast, reliable and intuitive software. You will work across the stack, collaborating closely with data scientists, risk analysts and product managers.

• What you’ll be doingDesigning, building and maintaining features across a Python back end and a JavaScript front end
• Turning research models and large datasets into scalable analytics services and APIs
• Building clear, interactive data visualisations and dashboards for finance, sustainability and risk users
• Working with data scientists to take models from prototype into production
• Contributing to architecture decisions, code reviews and engineering best practice
• Improving performance, reliability and test coverage across a cloud-hosted platform
• Supporting new product capabilities, including AI-driven features that let users query results in plain language

• What you’ll bringStrong commercial experience with Python for back-end or data-heavy applications (e.g. Flask, FastAPI, Django)
• Solid JavaScript skills; experience with React or a similar modern framework is a strong plus
• Experience with relational databases (PostgreSQL preferred) and designing APIs
• Familiarity with cloud platforms (AWS ideally), CI/CD and Git-based workflows
• Experience working with data-intensive or analytical applications
• A pragmatic, collaborative approach and the ability to explain technical trade-offs to non-engineers

• Nice to haveData visualisation libraries (e.g. Dash/Plotly, D3, charting libraries)
• Docker and infrastructure-as-code
• Exposure to scientific, financial or geospatial data
• An interest in climate, sustainability or risk modelling. No domain expertise is required.

• What’s on offerBonus scheme
• Pension
• Private medical care
• Flexible, hybrid working from a central Cambridge office
• The chance to make a real impact at a growing scale-up tackling climate risk
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