Cervest is building the world's first open access AI-powered Climate Intelligence platform.
We’re a Certified B Corporation with a vision to build a climate intelligent world — one where everyone is able to use Climate Intelligence to adapt with climate change. By making Climate Intelligence open, democratised and transparent we will power a global Climate Intelligent Network™ that drives a chain reaction of climate intelligent decisions to protect the world’s critical assets, including our greatest asset — the planet.
Using our flagship EarthScanTM product, anyone can discover how current and future climate events such as flooding, droughts, and extreme temperatures will impact their assets. EarthScan helps our customers confidently de-risk decisions, meet financial disclosure needs and improve the resilience of the assets they own, manage or rely on.
As a company, we are a pro-diversity, highly inclusive organization, committed to bringing together people of all backgrounds and enabling them to succeed. We know that a richly diverse team will help us achieve our mission sooner.
- Build and evaluate ML pipelines for Earth Science modelling, such as weather and climate downscaling, extreme events modelling, or physical risk estimation.
- Write clean, easy-to-understand code, and contribute to the team’s software engineering knowledge.
- Communicate complex scientific concepts simply but non-reductively to other teams and clients.
- Collaborate with designers and engineers to ensure that Science Team output is incorporated into the product as smoothly and optimally as possible.
- Read scientific papers to understand the current state-of-the-art for relevant modelling tasks, and attempt to replicate those papers where appropriate.
- Statistical, Machine Learning, or Deep Learning background, with industry experience.
- Solid software engineering skills, particularly relating to data engineering.
- Good scientific communication skills, able to explain technical concepts to a non-technical audience.
- Pragmatic approach to problem solving.
- Experience with Python.
- Experience working with geospatial data, ideally climate or weather data.
Bonus points for:
- Experience with Julia
- Experience in geospatial statistics, modelling physical systems, extreme value analysis, scalable Bayesian inference.
As a rapidly scaling company on a mission, we are committed to ensuring that we support our team in developing in line with their aspirations and talents as well as continuing to develop our culture in line with our values.
We are a remote-first company and are hiring across Europe, the USA and beyond. We are looking for a candidate who is comfortable working in a remote setting and with a diverse team distributed across multiple time zones. This job requires minimum travel for occasional regional or global team retreats only, using more sustainable transport methods (we’ll help with that) so generally within one time zone of the UK.
- 25 days’ holiday a year (plus 8 UK public holidays or local equivalent)
- The company closes between December 24th and January 1st, which typically gives an extra 3 days off each year (on top of your 25 days entitlement)
- Remote first company culture with flexible working hours
- Maternity, paternity, adoption or shared parental leave policies
- Every employee is given a plant of their choice
- £1000 a year learning budget towards personal and professional development
- 10% of your time can be used for projects that help us meet Cervest’s mission outside your day-to-day responsibilities
- £500 stipend to spend on your work from home setup (we’ll cover your laptop and peripherals such as a screen and keyboard - you will be able to choose between a Mac or PC)
- Paid sick leave for physical and mental health with access to Spill
- Virtual team and company activities such as pastry-making classes, mindfulness classes, coffee masterclasses and murder mysteries
- £1500 loan towards a bike through the Cycle to Work Scheme (available for UK employees)
Please contact us if you have a disability and need any adjustments to be made to the application or interview process