Statistical Scientist – Spatiotemporal and Gaussian Processes

Cervest

  • Full Time

To apply for this job please visit apply.workable.com.

Description

Cervest is building the world’s first open access AI-powered Climate Intelligence platform.

We’re a certified B-Corp with a vision to democratize access to Climate Intelligence driving a shared responsibility to protect the world’s critical assets — including our greatest shared asset, the planet.

It’s an exciting time to join us. We’ve just raised $30m in Series A investment. Our inaugural product, EarthScan™, will launch in 2021. EarthScan™ enables organizations to de-risk business decisions, meet financial disclosure guidelines, improve resilience, and uncover new opportunities to accelerate low-carbon growth.

We’re backed by leading venture capital firms, including Draper Esprit, Future Positive, Lowercarbon Capital, and Astanor Ventures. We are now building up our team in all areas: sales, marketing, science, engineering, and people operations.

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.

As a Statistical Scientist with focus on spatiotemporal modelling at Cervest, you will:

  • Build and evaluate ML pipelines for Earth Science modelling that capture spatiotemporal correlation structures within physical systems.
  • Write clean, easy-to-understand code.
  • Contribute to the team’s knowledge of spatiotemporal modelling.
  • 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

Required skills:

  • Statistical or Machine Learning background, with industry or research experience in spatiotemporal statistics and/or Gaussian process modelling.
  • 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 modelling physical systems, extreme value analysis, scalable Bayesian inference, uncertainty quantification.

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.

  • £50k-£70k
  • 22 days’ holiday a year (plus 8 UK public holidays or local equivalent)
  • The company closes between Christmas and New Year which gives an extra 3-4 days off each year (on top of your 22 days entitlement)
  • Remote first company culture
  • Flexibility in working times
  • £1000 each year to expand your development
  • Extensive home office budget
  • Paid sick leave for physical and mental health with access to Spill
  • Opportunities to learn, grow and thrive with support from talented and empathetic team mates
  • 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.