Maritime Alliance for fostering theEuropean Blue Economy through aMarine Technology Skilling Strategy

Professional and Soft Skills for Continuous Education of Data
Professionals to enable the Digital Transformation of companies
Industry 4.0 and Digital Transformation
Digital Competences and Skills

Digital Transformation• Digitation and IoT• Digitalisation of Processes• Optimisation and Simulation• Intelligent Information andKnowledge Management• Data Management Maturity• Digital Assets Manage• Agile Data Driven
Organisational Model• Customer Experience• People and skills

Big Data

Additive
Manufacturing• Information and data literacy• Managing data, information,knowledge• Digital content creation,programming• Digital security and safety• Communication and collaboration• Problem solving and critical thinking

SystemIntegration

Internet ofThings

Digital competence and skills aretransversal: Their effect spans from direct
professional activity at all levels to moregeneral attitude and entrepreneurship skills.
Multiple competence and skills groups
should be targeted by (continuous)
education and training

Data Analytics and Processes digitalisation are driving Industry 4.0
Data Scientist Professional Skills

21st Century or Workplace Skills

Thinking and Acting like Data Scientist

Top Skills for Future Data Driven Industry and Research• Complex Problem Solving• Critical Thinking• Creativity• People Management• Coordinating with Others, Negotiation• Emotional Intelligence• Judgment and decision making• Service Orientation, Customer focus• Working with tools and technologies• Dynamic (self-) re-skilling• Cognitive flexibility• Professional networking• Ethics and professional code of conduct
MATES Project Objectives and focus areas
MATES’ objective is to develop a skills strategy that addresses the main driversof change to the maritime industry, in particular shipbuilding and offshore
renewable energy. Both sectors are strongly linked and require new capacities tosucceed in an increasingly digital, green and knowledge driven economy.
Part of the EU Skills Agenda and the Blueprint for sectoral cooperation on skills.

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www.projectmates.eu
Co-funded by the Erasmus+ Programmeof the European Union

LONGTERMSKILLSSTRATEGY

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LITER
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1. Recognise value of data, work with raw data, exercise good data
intuition, use SN and open data
2. Accept (be ready for) iterative development, know when to stop,
comfortable with failure, accept the symmetry of outcome (bothpositive and negative results are valuable)
3. Good sense of metrics, understand importance of the results
validation, never stop looking at individual examples
4. Ask the right questions
5. Respect domain/subject matter knowledge in the area of datascience
6. Data driven problem solver and impact-driven mindset
7. Be aware about power and limitations of the main machine learningand data analytics algorithms and tools
8. Understand that most of data analytics algorithms are statistics andprobability based, so any answer or solution has some degree ofprobability and represent an optimal solution for a number ofvariables and factors
9. Recognise what things are important and what things are notimportant (in data modeling)
10.Working in agile environment and coordinate with other roles andteam members
11.Work in multi-disciplinary team, ability to communicate with thedomain and subject matter experts
12.Embrace online learning, continuously improve your knowledge, use
professional networks and communities
13.Story Telling: Deliver actionable result of your analysis
14.Attitude: Creativity, curiosity (willingness to challenge status quo),commitment in finding new knowledge and progress to completion
15.Ethics and responsible use of data and insight delivered, awarenessof dependability (data scientist is a feedback loop in data driven
companies)

Thematic Group Digitalisation and Digital Skills coordinator
Yuri Demchenko y.demchenko@uva.nl
MATES Project contact: info@projectmates.eu