We are TRASYS International, NRB Group, an ICT company with over 30 years of a successful track record working with European Institutions and Agencies, offering IT consulting, solutions and services. Our Mission is to help our clients keep up with the challenges of digital transformation by providing the right talent at the right time for the right job. To this end, we are constantly looking for talented professionals who are interested in working on challenging international projects and able to deliver high-quality results within multicultural environments. Our services include (but are not limited to) modernisation solutions, digital workspaces, cloud technologies and IT security. Our Headquarters are in Brussels, and we have active accounts and offices across Europe (i.e. Luxembourg, Amsterdam, Athens, Stockholm, Geneva).
We are currently searching for a Data Scientist / Database developer for one of our clients, an European Institution located in the north of Italy.
The objective of this position is to develop data processing workflows that improve our capacity to monitor biodiversity in rural landscapes. This requires:
- Organization and construction of a geospatial database with pictures, observations, and data collected through the module surveys (2018 and 2022) for automated computation and analysis;
- Implement and test a variety of existing machine learning algorithms and approaches to recognize flower/plant species on pictures;
- This includes developing a data extraction and impage processing chain that makes use of existing computer vision algorithms (e.g. Faster-R-CNN);
- Using data analytics to quantify biodiversity related characteristics automatically, number of flowers, flower size distribution, colour distribution, …
- Scripting to use the dedicated online API in batch mode to classify species on extracted (flower) image objects.
- Data analysis of biodiversity and species information in relation to habitat characterization, including the processing of geospatially gridded data and maps.
- Write technical documentation.
- MSc or engineering degree in relevant fields (computational ecology, computer science, physical geography, earth system science).
- Excellent knowledge of data analytics techniques and tools and proven experience with Python, Jupyter notebook, R.
- Advanced hands-on experience with python and specifically with libraries related to computer vision and machine learning (e.g. SciKit-Learn) and with the OpenCV 3.3 module and deep learning frameworks such as TensorFlow.
- Knowledge on trend/anomalies detection in datasets.
- Capability of integration in an international/multicultural environment and experience in working in team;
- Rapid self-starting capability, autonomous and accurate working style;
- Excellent team player;
- Ability to understand, speak, and write English C1 and Italian B1 will be an advantage.