Cyber Security, Data Science
Master (EQF 7)
NATO offers you more than a job. It gives you a mission: building peace and security for one billion people in Europe and North America. The NATO Communications & Information Agency (NCIA) is leading NATO’s Digital Endeavour. The role of Data Scientist will be part of the newly created Data Science services team based from The Hague, Netherlands.
Who we are:
NCIA acquire, deploy and defend communications systems for NATO's political decision-makers and Commands; the agency is on the frontlines against cyber-attacks, working closely with governments and industry to prevent future debilitating attacks.
We are NATO’s technology and cyber leaders, helping NATO Nations to communicate and work together in smarter ways. Our work is challenging and meaningful, and you will develop and apply your expertise as part of a dynamic international team of civilian and military professionals.
The new role of Data Scientist will part of a team which is responsible for the development and delivery of data science services across NATO, applying innovative technology to extract value from NATO data and enable NATO to make better decisions, faster.
This entry-level role to the NCIA Data Science community will support internal and external analysts, helping to maintain the Agency’s data stores and tools to process, analyse and learn from these highly diverse datasets. The Data Scientist will run processes and procedures related to data engineering, including those for data pipelines by supporting the maintenance of the Agency’s data lakes, implementing updates and working with system owners to ensure data is available for analysis.
This role will also:
- Contributes to the design and updates to the Agency’s data lakes, and data science approaches, in conjunction with the data science team and Service Line analysts;
- Contributes to the machine learning initiative across the Agency with suggestions for ML approaches and implementation, including the processing of training data and performance assessment of machine learning techniques on datasets;
- In conjunction with the Data Science Team, manage and update the Agency toolset for data analysis;
- Contributes to new/modifications to data science toolsets and metrics, and to machine learning toolsets and metrics;
- Contributes to pan-Agency data science capabilities to meet needs of the Agency and its customers;
What do we offer?
- Genuinely meaningful work as part of the most successful alliance in history
- Initial three year contract with competitive monthly tax-free salary* and household & children’s allowances
- Privileges for expatriate staff including expatriation and education allowances (where appropriate) and additional home leave
- Excellent private health insurance scheme
- Generous annual leave of 30 days plus official holidays
- Retirement Pension Plan
You show leadership skills and willingness to learn, and excel on analytical and problem solving skills, being able to think critically regarding systems, and what and how to develop innovative solutions using novel Data Science techniques. You are also comfortable performing different type of tasks, able to speak your mind as well as listen to others. In addition to this, you also have:
- MSc Data Science or associated course from a nationally recognised/certified University
- Experience applying data science tools to support advanced data analytics, machine learning and data visualisation. Experience should include two or more of the following technology areas:
- Experience in planning and executing Data Science process: Ingestion, Pre-processing, Analyzing, Post-processing and Vizualization;
- Application of state-of-the-art data science, analytics and data integration tools/programming languages on real-world datasets, for example: Python, KNIME, R, Splunk;
- Knowledge of mathematical and statistical models and practical experience with statistical packages e.g. from Python, R, KNIME etc;
- Use of data visualisation tools e.g. Microsoft Power BI, Spotfire, Tableau; Kibana;
- Experience with AI / machine learning tools e.g. Watson, Microsoft Cognitive Toolkit, TensorFlow;
- Use of Big Data ecosystems e.g. Hadoop, MapReduce, Spark.