Statistical Scientist

It’s an exciting time to join Cervest. Our inaugural product, EarthScanTM, will launch in 2021. EarthScanTM is an automated climate risk impact discovery tool that measures the impact of climate change on physical assets like buildings.

Backed by leading VCs in Europe and the US, Cervest is a climate tech company building the world’s first open access AI-powered Climate Intelligence platform.

Our platform will allow organisations to understand the climate risk across all their assets for any timescale and any scenario, anywhere on Earth. Data engineering plays a crucial role in making this vision a reality. The team supports the acquisition, ingestion, processing and hosting of any data and designs, and delivers infrastructure to support efficiency and innovation at scale.

As a company, we are a pro-diversity, highly inclusive organisation, 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.
As a Statistical Scientist at Cervest, you will:

• 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.

Requirements

• 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.

Benefits

Opportunities to learn, grow and thrive with support from talented and empathetic team mates

We are a remote first company and looking for candidates who would be able to come to our office in London (once travel is sensible) a few times a year using more sustainable transport methods (we’ll help with that) so generally within one time zone of the UK.

Fuller list of benefits on our main career page – we’re an early-stage startup and currently reviewing our benefits in light of becoming a remote-first company. 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.