Data Scientist: missions, skills, training, salary and career development

In recent years, the explosion of massive data and the rapid evolution of technologies have profoundly transformed many sectors. The growing importance of digitalisation and predictive analysis has led to the emergence of the Data Scientist profession. This professional plays a central role in exploiting and analysing large quantities of data to extract relevant information, thereby facilitating decision-making in an increasingly data-driven environment.

Description of the Data Scientist job

Data Scientists are experts in data management and analytics. They use advanced data mining, machine learning and statistical techniques to model and interpret data collected from various data sources. Their aim is to transform this data into customer knowledge and insights that can be used to improve the company's decision-making and strategic processes.

What is the role and remit of a Data Scientist?

Collecting and processing data

Data Scientists collect and prepare data from a variety of sources, both structured and unstructured. They use tools and programming languages such as SQL, Python and R to clean, transform and store this data in databases or data warehouses.

Analysis and modelling

They analyse data using advanced analysis techniques and create predictive models and algorithms to predict future trends. Analytical models often include regression, segmentation and classification methods.

Visualisation and reporting

Data Scientists use data visualisation tools such as Tableau, Power BI and Google Analytics to create interactive dashboards and reports that help decision-makers understand the results of analysis. These visualisations make it easier to communicate insights clearly and effectively.

Decision support

As a business intelligence expert, the Data Scientist plays a key role in decision support by providing detailed analyses that support the company's strategic decisions. They work closely with other departments, such as digital marketing, supply chain and operational management, to optimise processes and performance.

Tools and technologies used by Data Scientists

Environments and frameworks

Data Scientists work with frameworks such as Apache Spark, Hadoop and TensorFlow to manage and analyse large volumes of data. They also use cloud computing platforms such as AWS and Google Cloud to store and process masses of data.

Analysis and visualisation tools

They use analysis tools such as SAS, SPSS Modeler and Talend, as well as Python libraries such as pandas and scikit-learn for advanced analysis and machine learning. For data visualisation, tools such as Tableau and Power BI are commonly used.

What skills do you need to be a good Data Scientist?

Professional skills:

• Mastery of programming languages: Python, R, SQL.
• Knowledge of databases: relational and non-relational.
• Skills in statistics and mathematics: quantitative analysis, logistic regression, etc.
• Use of data mining tools and machine learning frameworks.

Personal skills:

• Analytical and critical thinking skills.
• Communication skills to explain complex concepts clearly.
• Initiative and the ability to work independently.

What are the current challenges facing a Data Scientist?

Data volume management

• Processing and analysing huge volumes of data from a variety of sources.
• Ensuring the quality of the data collected and processed.

Cybersecurity

• Protecting sensitive data against cyber threats.
• Compliance with data protection regulations.

Technological developments

• Keeping up to date with new data science technologies and methodologies.
• Integrating connected objects (IoT) and real-time data.

How do I become a Data Scientist?

Education and training

To become a Data Scientist, it is advisable to study between Bac+3 and Bac+5 in mathematics, statistics, computer science or data science. Here are a few possible courses:

• Bac+3: Bachelor's degree in computer science, Bachelor's degree in applied mathematics.
• Bac+5: Master's degree in Data Science, Specialised Master's degree in Big Data, MBA in Business Analytics.

EM Normandie offers courses tailored to this profession, in particular the MSc Artificial Intelligence for Marketing Strategy. This course provides the necessary skills in data science, machine learning and data analysis, offering a complete preparation for becoming a successful Data Scientist.

Professional certifications and continuing education, such as data science MOOCs, can also be very beneficial. Institutions such as Polytechnique or courses in business intelligence and big data are recommended.

Professional experience

Previous experience in data analysis or IT development is crucial. Internships, work-study schemes and personal projects are effective ways of gaining this experience.

What are the career prospects for a Data Scientist?

• Progression to Data Manager, Chief Data Officer (CDO) or Chief Information Officer (DSI).
• Opportunities in data science or business intelligence consulting firms.
• Possibility of becoming a trainer or independent consultant in data analytics.

What does a Data Scientist earn?

The salary of a Content Manager varies according to experience, the size of the company and the sector of activity:

• Beginner: Gross monthly salary (approx.): €3,000 - €4,000
• 2-5 years' experience: Gross monthly salary (approx.): €4,500 - €6,000
• 5+ years' experience: Gross monthly salary (approx.): €7,000 and more

Where does a Data Scientist work?

Data Scientists may work for:

• Technology companies: Google, Amazon, etc.
• Banks and insurance companies.
• Industries and retail companies.
• Consulting firms and start-ups specialising in data science.

In summary

The Data Scientist profession is essential for exploiting data and making strategic decisions. Versatile and technical, the Data Scientist plays a key role in analysing and modelling data to provide valuable insights. This profession offers interesting career prospects, with opportunities to progress to management positions or expert consultancy. The Data Scientist is an indispensable player in the Big Data sector, responding to the needs of businesses while adapting to technological and regulatory developments.