Modelling & AI Machine Learning Intern (May – August 2026)

BNP Paribas is a leading international banking institution committed to building a sustainable future. The Modelling & AI Machine Learning Intern will develop statistical and machine learning models, contribute to data analysis, and support various operational responsibilities within the ALM Treasury team.

Responsibilities

• You will contribute to the development, maintenance, and support of statistical models to predict customer behaviour (exercise of the option of early repayments, outflow of deposits, drawdown of off-balance sheet etc.) taking into account the evolution of the economic and financial environment, and Machine Learning models to forecast market rates and financial indicators changes
• You will leverage advanced python programming expertise to build robust data pipelines, scale ML models, and automate workflows
• You will use your experience with database technologies, version control and advanced statistical models to independently lead projects and proactively adapt to new challenges
• You will employ data visualization tools like Power BI to effectively monitor and improve the performance of machine learning models, ensuring operational efficiency and excellence
• You will contribute to ad-hoc analyses on liquidity and IR risk measurement, contribute to the team’s technology watch, and be agile to provide support other ALMT teams and other stakeholders (Risk) on a case-by-case basis

Skills

• Excellent skills in financial mathematics and data science
• Student in Master's degree in MIS, Computer Science, Optimization, Statistics or Mathematics
• Strong level python coding
• Experience with machine learning and deep learning libraries (e.g, Pandas, NLTK, SciPy, Scikit-learn, NumPy, Keras and TensorFlow)
• Design & develop data pipeline job
• Experience with database technologies and data query languages (SQL)
• Experience with code repository, version control tools such as Git/Bitbucket
• Familiarity with data visualization tools (Power BI) for building and monitoring ML models performance
• Experience with NLP, LLMs and Transfer learning
• Experience in statistics, regression models, random forests, and LSTM models
• Ability to work independently, to be proactive and to adapt
• Professional working proficiency in French and English languages are required

Benefits

• Competitive compensation
• Hybrid work arrangements
• Excellent training and personal development programs
• Opportunities for career development within the company and internationally

Company Overview