Environmental Data Scientist
- Crawley (other EU locations will be considered), United Kingdom
Where People, Data and Technology Meet
CGG is a pioneering Technology Company providing world class fully integrated Geoscience services globally. We employ in excess of 4,000 people worldwide, who bring a unique blend of talent and energy through working together to deliver unrivalled innovative solutions to our customers.
Through our cutting-edge Technology in Geoscience, we have achieved outstanding leadership with a strong focus on innovation and a commitment to delivering the best sustainable solutions to our clients' challenges. Our scientific teams collaborate with customers, through the analysis, enhancement and creative problem solving of complex data.
We are looking for enthusiastic and talented individuals to join our Environmental Science team based in South-East England (other European locations where CGG has offices would also be considered). This part of our business is expanding rapidly, and there are a number of opportunities available to support the collection, integration and analysis of data in order to derive insights and intelligence to mitigate environmental risks.
- Assess the effectiveness and accuracy of new data sources and data gathering techniques
- Provide ongoing and regular business related insights/analytics/metrics from vast volumes of existing public data (for example: government public data bases, satellite imaging and other 3rd party sources) in order to identify and quantify patterns and trends
- Use those insights to develop custom data models and algorithms to apply to data sets
- Mentoring wider team of Data Scientists
The successful candidate will have at least ten years’ experience in a data science role. Experience within the ESG sector or of working on projects within this sector (specifically, how companies quantify, manage and report on ESG issues) would be desirable. You will benefit from having some of the skills identified below:
- Advanced skills in Python:
- Data management and analysis: pandas, geopandas
- Data visualisation: matplotlib, seaborn, folium
- Strong knowledge of GIS analysis tools (ArcGIS, QGIS, etc)
- Advanced experience in integrating diverse types of data (satellites, drones, ground stations)
- Good understanding in statistics and machine learning model building
- Strong machine learning skills and tools: scikit-learn, TensorFlow, Keras, Pytorch
- Strong knowledge of machine learning methods and algorithms (random forest, neural networks, time-series, classification / regression and many others)
- The ability to define and manage project deadlines
- Excellent communication and collaboration skills with the ability and willingness to guide less experienced colleagues
- An enthusiastic attitude towards learning and flexibility to adapt to new challenges or changes in direction
- English language is a requirement, other language skills (especially Spanish) are desirable
- An understanding of, and experience of working with clients within investment, financial & insurance markets would be a benefit