Posted by BNP Paribas is a leading European bank with an international reach. It has a presence in 72 countries, with more than 202,000 Employees – including more than 154,000 in Europe and over 5,000 in Portugal alone. BNP Paribas is present in Portugal since 1985, having been one of the first foreign banks to operate in the country. Today, BNP Paribas has several entities operating directly in this territory, offering a wide range of integrated financial solutions to support its clients and their businesses.
BNP Paribas Careers Opportunities for Graduate Fresher, Entry Level, Mid Level role in various domain such as banking, finance, Capital market, Investment, Legal, HR, Operation, Customer services, sale, marketing and many more
BNP Paribas is a top-ranking bank in Europe with an international profile. It operates in 71 countries and has almost 199 000 employees. The Group ranks highly in its three core areas of activity: Domestic Markets and International Financial Services
Careers Opportunities for Graduate Entry Level 2026
Data Science Intern – India
Global Markets is currently recruiting talented people to join one of the most challenging and exciting part of our Quantitative Research team, the Data and Artificial Intelligence Lab!
We are currently recruiting interns (in Mumbai) for the Global Market Data and Artificial Intelligence Lab of BNP Paribas: Global Market is part of the Corporate and Investment Bank and deals with all market activities on Equity, Foreign Exchange and Local Markets, G10 Rates, Primary and Secondary Credit and Financing asset classes.
We are, among other things, building models to improve the service we give to our clients (issuing recommendation, anticipating their needs, bringing the relevant research…), to help traders better understanding and managing their risks or leverage alternative data sources (social media, news, images…) for the benefit of our strategists.
We are looking for candidates with education in data science, who not only have experience in solving complex problems but as well understand how and why the model work the way they do.
They need to be motivated with dealing with large amount of very diverse data and extracting valuable insights out of it.
The right candidate needs to be able to adapt quickly to new challenges, not to be afraid to experiment many times and fail before finding the right solution, challenge themselves with the feedback of the users and they will have the excitement of seeing their work being used in real live by the business.
For internships, we are looking at duration of 6 months and we are flexible on the starting date (the earlier the better!). The intern will participate to the life of the LAB and will take ownership of one or more topic.
We have a great variety of topics, and some of the historical propositions included:
· Prediction of which products are the most likely to be interesting for a given client.
· Automated Generation of Market Comment.
· Optimal Risk Management of Interest Rates Swap Risk.
· Regime disentanglement for financial mixture of experts models.
· Generative modelling for model control.
· Transformers for quantitative investment strategies.
Based on the skillset & business need, we can select a valuable proposition for you!
Direct Responsibilities
1. Explore and examine data from multiple diverse data sources.
2. Conceptual modeling, statistical analysis, predictive modeling and optimization design.
3. Data cleanup, normalization and transformation.
4. Hypothesis testing: being able to develop hypothesis and test with careful experiments.
Contributing Responsibilities
1. Help build workflows for extraction, transformation and loading of different data from a variety of sources and enable linking them to existing systems and datasets.
2. Ensure the integrity and security of data.
Qualification:
1. Education in data science, who not only have experience in solving complex problems but as well understand how and why the model work the way they do.
2. Knowledge of key concepts in Statistics and Mathematics such as Probability Theory, Inference, and Linear Algebra.
3. Knowledge or experience in Machine Learning procedures and tasks such as Classification, Prediction, and Clustering.
4. Programming skills in Python and knowledge of common numerical and machine-learning packages (NumPy, scikit-learn, pandas, Keras, TensorFlow, PyTorch, langchain).
5. Ability to write clear and concise code in python.
6. Intellectually curious and willing to learn challenging concepts daily.
7. Involvement with the Data Science community through platforms such as Kaggle, Numerai, Open ML, or others.
8. Knowledge of current Machine Learning/Artificial Intelligence literature.
Education Level: Bachelor’s Degree or Master’s Degree or equivalent
For more details to apply, Click here!