Data Scientist (Environmental/ Agronomic modelling)

At Uni Systems, we are working towards turning digital visions into reality. We are continuously growing and we are looking for a professional Data Scientist with Environmental/ Agronomic modelling to join our UniQue Ispra team.

In this role, you will have the opportunity to work closely with our customers in the public sector and you will be responsible for developing new business by identifying profitable opportunities, maintaining your client portfolio by building strong, long-lasting relationships, and monitoring the progress of the projects, with the aim to provide excellent client service and added value services.

What will you be bringing to the team?

• Definition of relevant re-analysed datastreams and climate scenarios to support assessments as request by partner DGs, and scientific collaborations
• Preparation of pan-European scenarios for freshwater quantity (LISFLOOD) and quality (SWAT) for combinations of planned measures, and future changes of climate, demography and land use
• Management of data streams and computing resources using scripts and programming languages
• Development and maintenance of model code and analysis scripts
• Coordination and review of output requests
• Reporting of model scenarios and results including regional outputs
• Analysis of water use output with regard to reported data
• Assistance with debugging of model and quality checking of model results
• Interaction with the business analysts, customer, users, project leaders and the developers

Requirements

What do you need to succeed in this position?

• Very good knowledge of water quality and quality modelling; hands-on capability for providing quality control for application of water quantity and water quality process models in river basins and at continental scale;
• Understanding of spatial geographical and hydrological data;
• Knowledge of the main used development languages (R, Python);
• Hands-on experience in statistical and risk analyses on processing geo-spatial data by using R, Python, CDO ;
• Good knowledge of quality assessments and quality control tests during the application of water quantity and quantity models.
• Good capacity of statistical and risk analyses on processing geo-spatial data by using R, Python, CDO;
• Ability to provide assistance in the implementation of the water quantity and quality software efficiently and fast
• Ability to give business and technical presentations, including tailor made graphics for presentation and publication.
• Ability to cope with fast changing technologies used in computing, modelling, and data analysis
• Capability to write clear and structured technical documents in English.