Infocomm TechnologyISCO 2511
Data scientist
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
Check yourself in a minute: data scientist
Rate 5 of the 60 essential skills of this occupation (European ESCO data). No account needed.
normalise data
manage research data
use data processing techniques
interpret current data
interact professionally in research and professional environments
About data scientist
As a data scientist, you will be at the heart of data-driven decision making in organizations, responsible for extracting meaningful insights from complex datasets and translating them into actionable recommendations. Your daily work involves identifying and acquiring data sources, cleaning and normalizing large datasets, building sophisticated mathematical and statistical models, and using advanced analytical techniques to uncover patterns and relationships. You will create compelling data visualizations and present your findings to both technical experts and non-technical stakeholders, ensuring that your insights drive strategic business decisions.
Your role is essential in today's data-centric economy, as companies across all sectors rely on data scientists to optimize operations, improve products, predict market trends, and manage risks. You will work with cutting-edge tools and technologies, applying knowledge of machine learning, statistics, and data engineering to solve complex real-world problems. The work requires a strong foundation in mathematics and computer science, combined with curiosity, creativity, and business acumen.
Data scientists are among the most sought-after professionals in Poland and globally, with strong salary prospects and excellent career advancement opportunities. You can specialize in areas like machine learning, business intelligence, or domain-specific analytics, and move into senior technical or leadership roles.
Key Work Functions
Core areas of responsibility for a data scientist.
1
Data Acquisition and Preparation
- Identify and locate relevant data sources from internal systems and external databases
- Extract, clean, and normalize large datasets to ensure data quality and consistency
- Manage research data and implement data governance procedures
- Merge multiple data sources and resolve inconsistencies in datasets
2
Statistical Analysis and Modeling
- Apply statistical modeling techniques to understand data distributions and relationships
- Build mathematical models and algorithms to solve analytical problems
- Perform quantitative analysis and empirical analysis on datasets
- Conduct statistical tests and validate model assumptions
- Use data processing techniques and apply appropriate statistical methods
3
Data Visualization and Communication
- Create compelling data visualizations using specialized tools and techniques
- Present findings and insights to technical and non-technical audiences
- Apply visual presentation techniques to make complex data understandable
- Draft scientific or academic papers and technical documentation
- Communicate data insights and recommendations to stakeholders
4
Machine Learning and Advanced Analytics
- Build and train machine learning models for prediction and classification tasks
- Perform data mining and extract meaningful patterns from large datasets
- Apply data engineering techniques to process and transform data efficiently
- Implement online analytical processing (OLAP) for business intelligence
5
Data Ethics and Data Science Strategy
- Ensure compliance with data ethics principles and privacy regulations
- Develop data models and define data structures for analytical purposes
- Recommend data-driven solutions and strategic applications of data insights
- Review scientific literature and stay current with data science methodologies
Do You Have the Skills for This Role?
Core competency requirements inferred from the occupation's skill profile. Take the free assessment to see how you match.
Must-Have Skills (Advanced)
Problem SolvingAdvanced
Sense MakingAdvanced
Digital FluencyAdvanced
Developing PeopleAdvanced
Transdisciplinary ThinkingAdvanced
Supporting Skills
Creative ThinkingIntermediate
CommunicationIntermediate
European Skills Framework
Skills and knowledge areas required for this occupation based on European classification.
Essential (60)
mathematical modellingmathematical modellingThe process of establishing a mathematical representation problem, such as equations, of a real-word to provide insights, discover new features about the problematic scenario, better understand the or...data miningdata miningThe methods of artificial intelligence, machine learning, statistics and databases used to extract content from a dataset.visual presentation techniquesvisual presentation techniquesThe visual representation and interaction techniques, such as histograms, scatter plots, surface plots, tree maps and parallel coordinate plots, that can be used to present abstract numerical and non-...data engineeringdata engineeringThe process of developing and constructing systems for implementing data collection and analysis at large scale.quantitative analysisquantitative analysisThe technique of employing statistical and mathematical modelling and measurement to represent a specific reality through numbers.data visualisation softwaredata visualisation softwareA computer tool or application that creates a graphical and visual representation of data, allowing a better understanding and interpretation of complex data through visual elements such as maps, char...statistical modeling techniquesstatistical modeling techniquesThe approaches for employing statistical analysis to dataset within the data science field. It seeks to elaborate reality predictions through statistical models and explicit assumptions.information extractioninformation extractionThe techniques and methods used for eliciting and extracting information from unstructured or semi-structured digital documents and sources.scientific literaturescientific literatureThe medium of informing the scientific community, including academic researchers, about the results of scientific research. It constitutes a permanent and cumulative collection of all the findings of ...statisticsstatisticsThe study of statistical theory, methods and practices such as collection, organisation, analysis, interpretation and presentation of data. It deals with all aspects of data including the planning of ...information categorisationinformation categorisationThe process of classifying the information into categories and showing relationships between the data for some clearly defined purposes.resource description framework query languageresource description framework query languageThe query languages such as SPARQL which are used to retrieve and manipulate data stored in Resource Description Framework format (RDF).online analytical processingonline analytical processingThe online tools which analyse, aggregate and present multi-dimensional data enabling users to interactively and selectively extract and view data from specific points of view.data ethicsdata ethicsThe subfield of ethics that assess whether data practices are considerable ethical. It assesses processes such as collecting, analysing and disseminating structured and unstructured data that might ne...empirical analysisempirical analysisThe evidence-based method that is used to analyse and interpret information with the aim of drawing conclusions about a specific issue.data modelsdata modelsThe techniques and existing systems used for structuring data elements and showing relationships between them, as well as methods for interpreting the data structures and relationships.draft scientific or academic papers and technical documentationdraft scientific or academic papers and technical documentationDraft and edit scientific, academic or technical texts on different subjects.normalise datanormalise dataReduce data to their accurate core form (normal forms) in order to achieve such results as minimisation of dependency, elimination of redundancy, increase of consistency.manage research datamanage research dataProduce and analyse scientific data originating from qualitative and quantitative research methods. Store and maintain the data in research databases. Support the re-use of scientific data and be fami...use data processing techniquesuse data processing techniquesGather, process and analyse relevant data and information, properly store and update data and represent figures and data using charts and statistical diagrams.interpret current datainterpret current dataAnalyse data gathered from sources such as market data, scientific papers, customer requirements and questionnaires which are current and up-to-date in order to assess development and innovation in ar...interact professionally in research and professional environmentsinteract professionally in research and professional environmentsShow consideration to others as well as collegiality. Listen, give and receive feedback and respond perceptively to others, also involving staff supervision and leadership in a professional setting.disseminate results to the scientific communitydisseminate results to the scientific communityPublicly disclose scientific results by any appropriate means, including conferences, workshops, colloquia and scientific publications.operate open source softwareoperate open source softwareOperate Open Source software, knowing the main Open Source models, licensing schemes, and the coding practices commonly adopted in the production of Open Source software.establish data processesestablish data processesUse ICT tools to apply mathematical, algorithmic or other data manipulation processes in order to create information.speak different languagesspeak different languagesMaster foreign languages to be able to communicate in one or more foreign languages.execute analytical mathematical calculationsexecute analytical mathematical calculationsApply mathematical methods and make use of calculation technologies in order to perform analyses and devise solutions to specific problems.evaluate research activitiesevaluate research activitiesReview proposals, progress, impact and outcomes of peer researchers, including through open peer review.demonstrate disciplinary expertisedemonstrate disciplinary expertiseDemonstrate deep knowledge and complex understanding of a specific research area, including responsible research, research ethics and scientific integrity principles, privacy and GDPR requirements, re...use databasesuse databasesUse software tools for managing and organising data in a structured environment which consists of attributes, tables and relationships in order to query and modify the stored data.handle data sampleshandle data samplesCollect and select a set of data from a population by a statistical or other defined procedure.increase the impact of science on policy and societyincrease the impact of science on policy and societyInfluence evidence-informed policy and decision making by providing scientific input to and maintaining professional relationships with policymakers and other stakeholders.manage findable accessible interoperable and reusable datamanage findable accessible interoperable and reusable dataProduce, describe, store, preserve and (re) use scientific data based on FAIR (Findable, Accessible, Interoperable, and Reusable) principles, making data as open as possible, and as closed as necessar...perform scientific researchperform scientific researchGain, correct or improve knowledge about phenomena by using scientific methods and techniques, based on empirical or measurable observations.build recommender systemsbuild recommender systemsConstruct recommendation systems based on large data sets using programming languages or computer tools to create a subclass of information filtering system that seeks to predict the rating or prefere...perform data cleansingperform data cleansingDetect and correct corrupt records from data sets, ensure that the data become and remain structured according to guidelines.apply for research fundingapply for research fundingIdentify key relevant funding sources and prepare research grant application in order to obtain funds and grants. Write research proposals.design database schemedesign database schemeDraft a database scheme by following the Relational Database Management System (RDBMS) rules in order to create a logically arranged group of objects such as tables, columns and processes.implement data quality processesimplement data quality processesApply quality analysis, validation and verification techniques on data to check data quality integrity.collect ICT datacollect ICT dataGather data by designing and applying search and sampling methods.apply research ethics and scientific integrity principles in research activitiesapply research ethics and scientific integrity principles in research activitiesApply fundamental ethical principles and legislation to scientific research, including issues of research integrity. Perform, review, or report research avoiding misconducts such as fabrication, falsi...promote open innovation in researchpromote open innovation in researchApply techniques, models, methods and strategies which contribute to the promotion of steps towards innovation through collaboration with people and organizations outside the organisation.publish academic researchpublish academic researchConduct academic research, in universities and research institutions, or on a personal account, publish it in books or academic journals with the aim of contributing to a field of expertise and achiev...promote the transfer of knowledgepromote the transfer of knowledgeDeploy broad awareness of processes of knowledge valorisation aimed to maximise the two–way flow of technology, intellectual property, expertise and capability between the research base and industry o...think abstractlythink abstractlyDemonstrate the ability to use concepts in order to make and understand generalisations, and relate or connect them to other items, events, or experiences.mentor individualsmentor individualsMentor individuals by providing emotional support, sharing experiences and giving advice to the individual to help them in their personal development, as well as adapting the support to the specific n...manage data collection systemsmanage data collection systemsDevelop and manage methods and strategies used to maximise data quality and statistical efficiency in the collection of data, in order to ensure the gathered data are optimised for further processing.manage personal professional developmentmanage personal professional developmentTake responsibility for lifelong learning and continuous professional development. Engage in learning to support and update professional competence. Identify priority areas for professional developmen...write scientific publicationswrite scientific publicationsPresent the hypothesis, findings, and conclusions of your scientific research in your field of expertise in a professional publication.deliver visual presentation of datadeliver visual presentation of dataCreate visual representations of data such as charts or diagrams for easier understanding.report analysis resultsreport analysis resultsProduce 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...develop professional network with researchers and scientistsdevelop professional network with researchers and scientistsDevelop alliances, contacts or partnerships, and exchange information with others. Foster integrated and open collaborations where different stakeholders co-create shared value research and innovation...integrate gender dimension in researchintegrate gender dimension in researchTake into account in the whole research process the biological characteristics and the evolving social and cultural features of women and men (gender).perform project managementperform project managementManage and plan various resources, such as human resources, budget, deadline, results, and quality necessary for a specific project, and monitor the project's progress in order to achieve a specific g...manage open publicationsmanage open publicationsBe familiar with Open Publication strategies, with the use of information technology to support research, and with the development and management of CRIS (current research information systems) and ins...synthesise informationsynthesise informationCritically read, interpret, and summarise new and complex information from diverse sources.conduct research across disciplinesconduct research across disciplinesWork and use research findings and data across disciplinary and/or functional boundaries.develop data processing applicationsdevelop data processing applicationsCreate a customised software for processing data by selecting and using the appropriate computer programming language in order for an ICT system to produce demanded output based on expected input.communicate with a non-scientific audiencecommunicate with a non-scientific audienceCommunicate about scientific findings to a non-scientific audience, including the general public. Tailor the communication of scientific concepts, debates, findings to the audience, using a variety of...data sciencedata scienceThe field of study that deals with big amount of data using AI techniques such as machine learning algorithms to predict patterns and obtain useful information to make business decisions.
Optional (33) — show
computer simulationcomputer simulationA programme run on a computer that represents dynamic responses of a system to explore a mathematical model behaviour, using a model of a real system, composed of mathematical equations.marketing analyticsmarketing analyticsThe set of processes for employing data to improve the effectiveness of marketing activities. It involves analysing metrics such as the Return on Investment (ROI) for identify opportunities of improve...business intelligencebusiness intelligenceThe tools used to transform large amounts of raw data into relevant and helpful business information.social network analysissocial network analysisThe research method that is mainly explored in sociology and communication science and focuses on the analysis of the relations between individuals and among organisations and states.XQueryXQueryThe 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 organis...image recognitionimage recognitionA process designed to detect and identify a feature or object in an image or video. This process is used in medical imaging, security surveillance or defect detection, among other fields. Key techniqu...scientific computingscientific computingThe interdisciplinary field between computer science, mathematics and engineering. It concerns the employment of technical approaches and theoretical frameworks, and the use of computers, to address i...SPARQLSPARQLThe 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 organis...research designresearch designThe set of methods and techniques of research that are used to conduct a study. It includes practical steps in research such as purpose statement, data collection, methodology, and data analysis.digital curationdigital curationThe field that deals with maintaining, preserving and adding value to digital research.business analyticsbusiness analyticsThe disciplines and technologies for solving business problems through employing quantitative methods such as data analysis and statistical models.multidisciplinary researchmultidisciplinary researchThe research technique where a common issue is investigated using approaches from different disciplines with the aim of finding a comprehensive solution to it.healthcare analyticshealthcare analyticsThe use of qualitative and quantitative methods to analyse patterns in healthcare data to the aim of improving healthcare administration, quality in patient care and diseases diagnosis.LDAPLDAPThe computer language LDAP is a query language for retrieval of information from a database and of documents containing the needed information.unstructured dataunstructured dataThe 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.LINQLINQThe 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.data quality assessmentdata quality assessmentThe process of revealing data issues using quality indicators, measures and metrics in order to plan data cleansing and data enrichment strategies according to data quality criteria.state estimationstate estimationThe process of fusing input data measurements and a mathematical model to determine the internal state of an energy system.computational biologycomputational biologyThe interdisciplinary scientific field that focus on employing data analytics and theories to investigate biological systems obtained through experiments.N1QLN1QLThe 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.manage ICT data classificationmanage ICT data classificationOversee the classification system an organisation uses to organise its data. Assign an owner to each data concept or bulk of concepts and determine the value of each item of data.use spreadsheets softwareuse spreadsheets softwareUse software tools to create and edit tabular data to carry out mathematical calculations, organise data and information, create diagrams based on data and to retrieve them.perform data miningperform data miningExplore large datasets to reveal patterns using statistics, database systems or artificial intelligence and present the information in a comprehensible way.integrate ICT dataintegrate ICT dataCombine data from sources to provide unified view of the set of these data.teach in academic or vocational contextsteach in academic or vocational contextsInstruct students in the theory and practice of academic or vocational subjects, transferring the content of own and others' research activities.manage ICT data architecturemanage ICT data architectureOversee regulations and use ICT techniques to define the information systems architecture and to control data gathering, storing, consolidation, arrangement and usage in an organisation.define data quality criteriadefine data quality criteriaSpecify the criteria by which data quality is measured for business purposes, such as inconsistencies, incompleteness, usability for purpose and accuracy.design database in the clouddesign database in the cloudApply design principles for an adaptive, elastic, automated, loosely coupled databases making use of cloud infrastructure. Aim to remove any single point of failure through distributed database design...manage datamanage dataAdminister all types of data resources through their lifecycle by performing data profiling, parsing, standardisation, identity resolution, cleansing, enhancement and auditing. Ensure the data is fit ...apply blended learningapply blended learningBe familiar with blended learning tools by combining traditional face-to-face and online learning, using digital tools, online technologies, and e-learning methods.make data-driven decisionsmake data-driven decisionsCollect data such as Key Performance Indicators (KPIs) for an organisation and use the information to formulate actions and strategies.create data modelscreate data modelsUse specific techniques and methodologies to analyse the data requirements of an organisation's business processes in order to create models for these data, such as conceptual, logical and physical mo...HadoopHadoopThe open-source data storing, analysis and processing framework which consists mainly in the MapReduce and Hadoop distributed file system (HDFS) components and it is used to provide support for managi...
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Frequently asked questions
What does a data scientist do?
Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.
What skills does a data scientist need?
A data scientist needs 60 essential skills, including mathematical modelling, data mining, visual presentation techniques, data engineering, quantitative analysis.
Will AI replace data scientist jobs?
The AI disruption score for data scientist is 81/100 (very high risk). Skills most exposed to automation: information categorisation, normalise data, image recognition. Most resilient: mentor individuals, interact professionally in research and professional environments, develop professional network with researchers and scientists.
AI Replacement Risk
81/ 100
Very High Risk
Low riskHigh risk
Skills most at risk from AI
Skills resilient to automation
This is the average for the whole occupation. The AI Career Shield test (about 10 minutes) shows the risk in your own work and what you can do about it.
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SectorInfocomm Technology
ISCO GroupInformation and communications technology professionals
Essential Skills60
Core Skills7
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