Computer scientist

Computer scientists conduct research in computer and information science, directed toward greater knowledge and understanding of fundamental aspects of ICT phenomena. They write research reports and proposals. Computer scientists also invent and design new approaches to computing technology, find innovative uses for existing technology and studies and solve complex problems in computing.

Includes people performing in-house research activities.
Excludes people performing outsource research activities.

The following job titles also refer to computer scientist:

IT scientist
ICT science researcher
computers scientist
ICT scientist
ICT research scientist
computer scientist
IT research scientist
IT researcher
IT science researcher
ICT researchers
ICT researcher

Master’s degree is generally required to work as computer scientist. However, this requirement may differ in some countries.

ISCO skill level is defined as a function of the complexity and range of tasks and duties to be performed in an occupation. It is measured on a scale from 1 to 4, with 1 the lowest level and 4 the highest, by considering:

• the nature of the work performed in an occupation in relation to the characteristic tasks and duties
• the level of formal education required for competent performance of the tasks and duties involved and
• the amount of informal on-the-job training and/or previous experience in a related occupation required for competent performance of these tasks and duties.

Computer scientist is a Skill level 4 occupation.

These occupations, although different, require a lot of knowledge and skills similar to computer scientist.

ICT research consultant
ICT research manager
data scientist
data analyst
user experience analyst

These occupations require some skills and knowledge of computer scientist. They also require other skills and knowledge, but at a higher ISCO skill level, meaning these occupations are accessible from a position of computer scientist with a significant experience and/or extensive training.

This knowledge should be acquired through learning to fulfill the role of computer scientist.

Scientific research methodology: The theoretical methodology used in scientific research involving doing background research, constructing an hypothesis, testing it, analysing data and concluding the results.

These skills are necessary for the role of computer scientist.

Conduct literature research: Conduct a comprehensive and systematic research of information and publications on a specific topic. Present a comparative evaluative literature summary.
Write research proposals: Synthetise and write proposals aiming to solve research problems. Draft the proposal baseline and objectives, the estimated budget, risks and impact. Document the advances and new developments on the relevant subject and field of study.
Execute analytical mathematical calculations: Apply mathematical methods and make use of calculation technologies in order to perform analyses and devise solutions to specific problems.
Apply statistical analysis techniques: Use models (descriptive or inferential statistics) and techniques (data mining or machine learning) for statistical analysis and ICT tools to analyse data, uncover correlations and forecast trends.
Conduct scholarly research: Plan scholarly research by formulating the research question and conducting empirical or literature research in order to investigate the truth of the research question.
Conduct quantitative research: Execute a systematic empirical investigation of observable phenomena via statistical, mathematical or computational techniques.
Conduct research interview: Use professional researching and interviewing methods and techniques to gather relevant data, facts or information, to gain new insights and to fully comprehend the message of the interviewee.
Execute ict user research activities: Perform research tasks such as recruitment of participants, scheduling of tasks, collecting of empirical data, data analysis and production of materials in order to assess the interaction of users with an ICT system, program or application.
Apply reverse engineering: Use techniques to extract information or disassemble an ICT component, software or system in order to analyse, correct and reassemble or reproduce it.
Synthesise research publications: Read and interpret scientific publications that present a research problem, the methodology, its solution and hypothesis. Compare them and extract the information needed.
Conduct qualitative research: Gather relevant information by applying systematic methods, such as interviews, focus groups, text analysis, observations and case studies.

This knowledge is sometimes, but not always, required for the role of computer scientist. However, mastering this knowledge allows you to have more opportunities for career development.

Business intelligence: The tools used to transform large amounts of raw data into relevant and helpful business information.
Mdx: The computer language MDX is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Microsoft.
Data mining: The methods of artificial intelligence, machine learning, statistics and databases used to extract content from a dataset.
Behavioural science: The investigation and analysis of subject behaviour through regulated and lifelike observations and disciplined scientific experiments.
Innovation processes: The techniques, models, methods and strategies which contribute to the promotion of steps towards innovation.
Documentation types: The characteristics of internal and external documentation types aligned with the product life cycle and their specific content types.
Xquery: The computer language XQuery is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the international standards organisation World Wide Web Consortium.
Emergent technologies: The recent trends, developments and innovations in modern technologies such as biotechnology, artificial intelligence and robotics.
Sparql: The computer language SPARQL is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the international standards organisation World Wide Web Consortium.
Information extraction: The techniques and methods used for eliciting and extracting information from unstructured or semi-structured digital documents and sources.
Information categorisation: The process of classifying the information into categories and showing relationships between the data for some clearly defined purposes.
Resource description framework query language: The query languages such as SPARQL which are used to retrieve and manipulate data stored in Resource Description Framework format (RDF).
Query languages: The field of standardised computer languages for retrieval of information from a database and of documents containing the needed information.
Ldap: The computer language LDAP is a query language for retrieval of information from a database and of documents containing the needed information.
Unstructured data: The information that is not arranged in a pre-defined manner or does not have a pre-defined data model and is difficult to understand and find patterns in without using techniques such as data mining.
Linq: The computer language LINQ is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Microsoft.
N1ql: The computer language N1QL is a query language for retrieval of information from a database and of documents containing the needed information. It is developed by the software company Couchbase.

These skills and competences are sometimes, but not always, required for the role of computer scientist. However, mastering these skills and competences allows you to have more opportunities for career development.

Create solutions to problems: Solve problems which arise in planning, prioritising, organising, directing/facilitating action and evaluating performance. Use systematic processes of collecting, analysing, and synthesising information to evaluate current practice and generate new understandings about practice.
Perform data mining: Explore large datasets to reveal patterns using statistics, database systems or artificial intelligence and present the information in a comprehensible way.
Innovate in ict: Create and describe new original research and innovation ideas within the field of information and communication technologies, compare to the emerging technologies and trends and plan the development of new ideas.
Develop professional network: Reach out to and meet up with people in a professional context. Find common ground and use your contacts for mutual benefit. Keep track of the people in your personal professional network and stay up to date on their activities.
Report analysis results: Produce research documents or give presentations to report the results of a conducted research and analysis project, indicating the analysis procedures and methods which led to the results, as well as potential interpretations of the results.
Process data: Enter information into a data storage and data retrieval system via processes such as scanning, manual keying or electronic data transfer in order to process large amounts of data.

2511 – Systems analysts

 

 

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References

1. Computer scientist – ESCO