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.
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.
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
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
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
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
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)
Supporting Skills
European Skills Framework
Skills and knowledge areas required for this occupation based on European classification.
Essential (60)
Optional (33)
Related Occupations
Other occupations in the Other category that share similar skill requirements.