Senior Applied AI Scientist

Read on to fully understand what this job requires in terms of skills and experience If you are a good match, make an application.Location:

UK-based, remote-first (with monthly optional meetups in London)Start date:

ASAPEligibility:

Must have the right to work in the UK

Overview

DeepRec.ai has the pleasure of partnering with a remote-first NbS startup as they look to hire a

Senior Applied AI Scientist

to lead the development of ML-driven solutions that scientifically quantify the real-world impact of nature-based interventions. You''ll join a multidisciplinary team of AI scientists, engineers, and environmental experts tackling one of the biggest challenges of our time: building trusted, scalable tools for climate and biodiversity action.

The CultureShared purpose, no ego.Remote-first with flexible working hours, built on trust.Monthly team meetups at a London-based office (Highbury).Clear communication, fast iteration, and support over silos.A culture that thrives on ambiguity, feedback, and a growth mindset.What You’ll DoDesign, build, and scale machine learning models using environmental and observational data.Apply advanced causal inference techniques such as Bayesian Neural Networks, Gaussian Processes, Difference-in-Differences, and Synthetic Control methods.Leverage foundation models (e.g. Prithvi, Clay) and transformers to extract insights from complex datasets.Work cross-functionally with science, engineering, and product teams to embed models into real-world pipelines.Communicate scientific and technical concepts clearly to both technical and non-technical audiences.Stay current with the latest developments in AI and environmental science, integrating relevant innovations into production.Mentor junior team members and foster best practices in applied ML.What You BringStrong background in applied machine learning, bayesian statistics, and causal inference.Proficiency in Python and ML frameworks such as PyTorch.Experience with cloud infrastructure (e.g., AWS, GCP).A clear, concise communication style - clear examples given when asked, not word salad.An adaptive mindset and comfort working in fast-changing environments.A deep motivation to contribute to climate and ecological impact.An advanced degree (MSc or PhD) in Computer Science, Statistics, Economics, Physics, Mathematics, or a related field.Nice to HaveExperience working with geospatial or spatial-temporal data.Experience with remote sensing datasets (e.g., Landsat, Sentinel, SAR).Familiarity with TorchGeo or TerraTorch.Experience with Rasterio, Geopandas, Xarray, or Dask.Previous collaboration with academic or scientific research communities.Publications in peer-reviewed journals or conferences.BenefitsRemote-first and flexible hours32 days paid holiday (including bank holidays, fully flexible)Extra day off on your birthdayPension schemeEnhanced gender-neutral parental leaveSpill mental wellbeing supportCompany laptop + home working setup allowance