Tout savoir sur le métier de consultant RSE
Data Scientist
Based in Paris, France
Full time position, local contract
Beginning: ASAP 2024
WHO WE ARE
PUR is a global leader in supply chain sustainability. We develop socio-environmental projects within the supply chains of our Corporate Partners. Through the economic and social empowerment of local communities and the introduction of sustainable development initiatives at the agricultural level, PUR seeks to address climate change, while regenerating and preserving the ecosystems upon which these supply chains depend. Many of PUR's projects fall within the categories of insetting, regenerative agriculture, agroforestry, forest conservation and landscape restoration. PUR is a B Corp Company which employs over 200 people and has a presence in 10 countries.
www.pur.co
The Data Scientist will help us leverage our field and tree species information, translating it into the carbon impact we are making in the world. They will integrate the Data Team and work closely to the Carbon team as well. They will use the extensive data we have to create models that will guide our project design, contracts, and state-of-the-art carbon modeling that is better suited to the reality of agroforestry projects in tropical areas.
Your responsibilities will include in a non-exhaustive manner :
Implement and optimize Machine Learning (eventually Deep Learning) models.
Work with structured and unstructured data (geospatial and image data).
Process and treat large volumes of information to generate insights and train models.
Implement and maintain Python codes.
Create dashboards and visualizations to show what the data says;
Develop and maintain a species-based carbon forecast and quantification tool.
Perform statistical analysis to evaluate uncertainty of forecast, drafting possible scenarios of carbon sequestration figures.
Pinpoint the best plots to use as sample plots for the carbon quantification, based on their representativeness of our projects.
Continuous improvement of the model and analysis of forecasted results based on new data coming in (Project Dashboards/ Long-Term Monitoring/ Verification & Data Mining).
Provide internal consultancy, using the created models, on best project design meeting carbon obligations (based on carbon analysis) & others relevant impacts (biodiversity / livelihoods / crop yields / water).
