About BNP Paribas Group:
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 (whose retail banking networks and financial services are grouped together under Retail Banking & Services) and Corporate & Institutional Banking, centred on corporate and institutional clients. The Group helps all of its clients (retail, associations, businesses, SMEs, large corporates and institutional) to implement their projects by providing them with services in financing, investment, savings and protection. In its Corporate & Institutional Banking and International Financial Services activities, BNP Paribas enjoys leading positions in Europe, a strong presence in the Americas and has a solid and fast-growing network in the Asia/Pacific region.
About BNP Paribas India Solutions:
Established in 2005, BNP Paribas India Solutions is a wholly owned subsidiary of BNP Paribas SA, a leading bank in Europe with an international reach. With delivery centers located in Bengaluru, Chennai and Mumbai, we are a 24x7 global delivery center. India Solutions services three business lines: Corporate and Institutional Banking, Investment Solutions and Retail Banking for BNP Paribas across the Group. Driving innovation and growth, we are harnessing the potential of over 6000 employees, to provide support and develop best-in-class solutions.
About Business line/Function :
The Data and Artificial Intelligence LAB is a team setup in 2016 with the mandate to build the next generation of Data Intelligence and language understanding products used in BNP Paribas Global Markets. Today we are a team of around 30+ Data Scientists based in Paris, London, Frankfurt, Lisbon, New York and Singapore and now expanding to Mumbai.
Job Title:
Senior Associate – Data Scientist
Date:
Department:
Front Office Support
Location:
Mumbai
Business Line / Function:
Global Markets – Data & AI Lab
Reports to:
(Direct)
Grade:
(if applicable)
(Functional)
Number of Direct Reports:
NA
Directorship / Registration:
NA
Position Purpose
Our goal is to deliver Machine Learning based solutions for the Global Market activity. Our main sponsors are trading, sales, structuring or strategists.
We use Machine Learning in four different types of context:
- To automate some easy and repetitive tasks, freeing up some time of our users to concentrate on more challenging tasks.
- To speed up or simplify some process: Machine Learning can help to replace a task already automated but slow and heavy by something faster or easier to maintain: indeed, sometimes it is easier to maintain data examples, than maintaining some code!
- To scale a process well done by humans but requiring a lot of time to take a decision: in this case we use Machine Learning to pre-process as much as possible the information and present it in a digestible manner, allowing him to take faster decisions, to be more systematic and to scale to more situations or opportunities. Large Language Models like ChatGPT, Mistral... will be a key enabler for those tasks.
- To predict what may happen in the future, by ingesting large amount of data in a very short time, a task that is usually extremely difficult for a human. It is usually based on time series.
Responsibilities
1. Explore and examine data from multiple diverse data sources.
2. Conceptual modeling, statistical analysis, predictive modeling and optimization design.
3. Understand and work around limitations in analytic models.
4. Data cleanup, normalization and transformation.
5. Hypothesis testing: being able to develop hypothesis and test with careful experiments.
6. Discover hidden insights/embedded patterns and enable business stakeholders to make decisions that are more informed.
7. 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.
8. Ensure the integrity and security of data.
9. Maintain proper collaboration and communication with the rest of the team world-wide.
10. Provide support for the daily production of the models delivered by the Mumbai team but potentially as well for other models to any of the Asian/EU/US time zones.
Technical & Behavioral Competencies
1. Qualifications: Bachelors / Master / PhD degree in Computer Science / Data Science / other science or engineering field.
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 big data solutions (Kibana, Hadoop, Spark) is a plus.
9. Proven record of having successfully carried out independent research from exploring large datasets.
10. Knowledge of current Machine Learning/Artificial Intelligence literature.
11. Wide IT culture: OS, parallelization, network, software engineering, new languages.
Skills Referential
Behavioural Skills:
Ability to collaborate / Teamwork
Critical thinking
Communication skills - oral & written
Attention to detail / rigor
Transversal Skills:
Analytical Ability
Education Level:
Bachelor Degree or higher
Experience Level
At least 1 year
