As a geospatial data scientist, you will be part of ButterFly, one of AXA Climate’s asset. ButterFly aims at building products focused on the value at risk of our clients to support our different Speed-Boats.
ButterFly is organized in Feature Teams, gathering data scientists and data engineers and covering different climatic risks such as floods, wildfires, droughts, cyclones, etc. The products developed by these Feature Teams mostly rely on geospatial data and deliver a wide range of world-wide services for the Speed-Boats: risk and vulnerability assessment, early and real-time detection and analysis, forecasting, damage assessment, etc.
Under the supervision of the Leaders of the Feature Teams Wildfires and Floods, you will contribute as a geospatial data scientist to deliver high-quality products with the two main following responsibilities:
· Data acquisition
· Identification of the relevant databases or the relevant providers available on the market.
· Acquisition and integration of these relevant databases to our data platform.
· Analysis & Modelling
· Review state of the art methods in the literature.
· Identification and benchmark of relevant providers of built-in solutions.
· Analysis and cross-comparison of various data sources.
· Construction of complex indexes by crossing together different data sources.
· Development of a wide range of algorithms: detection algorithm, forecasting models, damage assessment algorithms, etc.
· Integration of these algorithms and models in our data platform.
· Grandes Écoles d’Ingénieurs (X, CentraleSupélec, École des Ponts, Mines, ENTPE, ENSTA, ENSAE…)
· MSc in top French, European or International Universities (Paris-Saclay, Dauphine, Imperial College, ETH Zurich, EPF Lausanne…)
· Major in Data Science, Statistics or Modelling.
· 2-3 years of experience in data science.
· Previous experience with geospatial data is a strong advantage.
· Previous experience in data engineering is an advantage.
· Fluency in English required.
· Fluency in French desired.
· Strong scientific skills in Statistics and Probabilities – especially in timeseries.
· Strong skills in Python.
· Skills in geospatial databases such as netcdf or h5 format, and python geospatial libraries such as geopandas, shapely, etc.
· Programming skills – software oriented.
· Pragmatic, Solution-oriented & Autonomous.
· Demonstrated interest for climate and climate change issues.