By joining our Research Team at Crédit Agricole CIB, you will be part of a dynamic, collaborative and innovative environment where data is the driving force behind our decisions. You will get involved in projects from conception to deployment, giving you a comprehensive understanding of the entire data lifecycle. You will have the opportunity to collaborate with teams across different regions, markets and sectors, gaining a global perspective on how data drives business decisions.

Summary

Crédit Agricole CIB Global Markets Research is an international team of 40 research professionals in 8 major financial centres, dedicated to building close relationships with our clients and providing personalised analysis. We are expanding our data team to further leverage our expertise in rates, credit, FX, Emerging and Equity markets as well as our data infrastructure built over the years.

• The team closely works with analysts, strategists, traders and clients, with the objective of bringing added value and investment solutions in all areas covered.

• The new team member's main objective will be to expand our scope of macroeconomic and sectoral data (Industrials, ESG, Retail, Autos, Emerging Markets…). The intern will contribute to the ongoing development of the data infrastructure and support various teams in their data needs, including data extractions, transformations, and analysis.

Key Responsibilities

As a Data Engineer/Data Analyst Intern on the Research-Quants team, you will be on charge on these following tasks:

Data extraction and integration:

• Collect data from various sources, including databases, APIs and then integrate them into our central data system
• Clean and format the collected data to ensure consistency and usability. 
• Participate in the development and optimization of data models and schemas for efficient storage and retrieval.
• Develop scripts to automate data updates.

Data quality assurance and documentation:

• Conduct regular checks to ensure the accuracy and integrity of the data being processed
• Create and maintain comprehensive documentation for all data extraction, integration, and automation processes.
• Assist in the development of data quality metrics and dashboards to monitor ongoing data integrity.

Collaboration and reporting:

• Work closely with analysts to understand their data needs and ensure integration into the data infrastructure.
• Prepare reports and visualizations to present the results of the data extraction and integration processes.

Research and innovation:

• Suggest new tools or methodologies to improve existing workflows.

Active participation in NLP project:

• Contribute to an ongoing Natural Language Processing (NLP) project by supporting data collection, pre-processing, and annotation.
• Assist in the training and evaluation of NLP models, ensuring the use of relevant and high-quality data.
• Participate in research and experimentation to explore new NLP techniques and approaches

Our commitment to you

Join our team at Crédit Agricole CIB, the corporate and investment banking arm of 10th largest banking group worldwide in terms of balance sheet size (The Banker, July 2023). We offer more than just a job.

You will be part of a dynamic and collaborative work environment where CSR is embraced in our day-to-day business operation, innovation is encouraged and diversity is celebrated.

Crédit Agricole CIB, the first French bank to have committed to the Equator Principles, is a pioneer and global leader in sustainable finance. Our commitment to sustainability and corporate responsibility means that your work will have a positive impact on our communities and the environment.

With a people-centric culture where everyone is valued, and opportunities for personal and professional growth, Crédit Agricole CIB is not just a place to work – it is where you make an impact.

Our hiring process is open to all and should you have any particular needs or you may require adjustments, please let us know.

Graduate

• Experience with Power BI or other data visualization tools

• Understanding of data modelling concepts and techniques to design efficient data structures

• Good understanding of IA models, with a focus on NLP models

• Excellent analytical and communication skills
• Autonomous and with a strong sense of team spirit
• Organized ,rigorous and curious to learn about the financial environment

• Proficiency in Python, SQL, GIT, C#