The profession of Data Scientist in insurance or banking
The Data Scientist in insurance or banking leverages artificial intelligence algorithms and statistical models to analyze and interpret complex data.
With skills in machine learning, big data, and database management, they provide solutions to corporate challenges. Whether for improving risk management, detecting fraud, or personalizing offers, the data scientist plays a key role in the strategy of financial institutions.
Role and responsibilities of the Data Scientist in insurance or banking
The primary mission of the Data Scientist in the insurance or banking sector is to analyze financial and behavioral data to help companies better understand their clients, markets, and risks.
Using data processing tools and artificial intelligence, they develop predictive models that optimize business strategies and proactively address user needs.
Daily tasks
The main missions of the Data Scientist in insurance or banking are as follows:
- Collect, clean, and analyze financial, client, or market data.
- Develop machine learning algorithms to model customer behavior and predict risks.
- Optimize business processes through advanced data analysis (fraud detection, credit scoring).
- Visualize results through dashboards and indicators to facilitate decision-making.
- Collaborate with IT, marketing, and risk management teams to implement data-driven solutions.
- Monitor model performance and adjust algorithms based on market changes and new data.
Salaries and career progression
Early in their career, a Data Scientist in insurance or banking in France can expect an annual gross salary between €45,000 and €55,000.
With experience, this salary can exceed €80,000, or even more for positions with greater responsibility in large companies.
Career advancement opportunities include roles such as lead data scientist, head of data teams, or innovation director in the finance and insurance sectors.
Required skills
- Proficiency in machine learning and artificial intelligence techniques
- Advanced skills in statistics and data analysis
- Expertise in programming (Python, R, SQL) and database manipulation
- Knowledge of financial products and insurance-related issues
- Ability to develop predictive algorithms and scoring models
- Analytical mindset and ability to simplify complex results for decision-making
What studies are required to become a Data Scientist in insurance or banking ?
To become a data scientist in the insurance or banking sector, it is necessary to pursue specialized training in data science, applied mathematics, or computer engineering.
A master's degree (bac+5) is generally required, and skills in programming (Python, R) and database management (SQL) are essential for this role.
Training to Become a Data Scientist in Insurance or Banking at Université Paris Dauphine-PSL
Université Paris Dauphine-PSL offers suitable programs to become a data scientist in insurance or banking. The Master 2 Statistical and Financial Engineering provides technical expertise in data analysis and artificial intelligence, while addressing specific challenges in the financial sectors.