The tasks of a data scientist
In the age of massive data and artificial intelligence,the importance of the data scientist has become crucial for a large number of companies and organisations. They are experts at transforming raw data into actionable information to help make strategic decisions. Here are their main tasks:
Data collection
Data scientists identify and gather data from a variety of internal and external sources. They use data collection tools and techniques to obtain relevant data sets.
Data cleansing and preparation
They clean and prepare the data for analysis by dealing with missing values, errors and duplicates. This includes transforming the data into formats suitable for analysis.
Exploratory data analysis
Data scientists carry out exploratory data analysis (EDA) to understand the characteristics of the data and identify trends, patterns and relationships between variables.
Statistical modelling and machine learning
They build and implement statistical models and machine learning algorithms to predict results, classify data and discover insights. They use programming languages (Python, R) and tools such as TensorFlow, Scikit-learn, etc.
Data visualisation
Data scientists create data visualisations to communicate results clearly and effectively. They use visualisation tools such as Tableau, Power BI and matplotlib.
Interpreting and communicating results
They interpret the results of the analyses and communicate them to stakeholders in the form of reports, presentations and interactive dashboards.
Development of data-driven solutions
Data scientists develop solutions and recommendations based on data analysis to solve specific problems and improve decision-making processes.
The skills required
This field requires a wide range of skills. To be a data scientist, you will need :
- Technical: mastery of programming languages such as Python, R, SQL and machine learning and data science tools.
- Statistics and mathematics: in-depth knowledge of statistical concepts and modelling techniques.
- Data manipulation: experience with databases, data management tools and data extraction and transformation (ETL) techniques.
- Data visualisation: ability to create clear and informative visualisations to communicate results.
- Communication: ability to explain complex technical concepts in a way that is accessible to non-specialists.
- Problem solving: ability to tackle complex problems analytically and develop innovative solutions.
The working environment
Data scientists work in a variety of environments, including :
- Large companies and multinationals.
- Technology start-ups.
- Financial institutions.
- Consulting firms.
- Public sector and administrations.
- E-commerce companies.
- Research laboratories.
- Independent consultants.
Career development
With several years’ experience, data scientists can progress to positions of responsibility, such as lead data scientist, data project manager, chief data officer (CDO) or chief technology officer (CTO). They can also specialise in areas such as deep learning, predictive analysis or data science applied to specific sectors.
This is an essential and constantly evolving profession. It offers numerous opportunities for career development and specialisation in a sector of vital importance to a company, where data plays a central role in decision-making and innovation.
Average salary for data scientists
The salary of data scientists can vary depending on a number of factors, including experience, qualifications and the size of the company. Generally speaking, an expert in this field can earn :
- between €45,000 and €60,000 a year at the start of their career,
- between €60,000 and €80,000 a year after several years’ experience,
- between €80,000 and €100,000 annually as a senior employee.
Become a Data Scientist
Are you interested in this profession? Our ESEO school offers a range of courses and options to help you become a Data Scientist.