The Data Scientist will develop AI solutions, focusing on machine learning and NLP to improve processes and products, collaborate with teams, and uphold best coding practices.
Company Description
At Coface we make trade happen everyday
Our 5,200 experts representing 80+ nationalities in 58 countries are united by a shared purpose: helping companies navigate through uncertainty by empowering them to make the right decisions and trade smarter in a complex world.
With nearly 80 years of global experience, we offer companies a full range of solutions: Trade Credit Insurance, Business Information, Debt Collection, Single Risk insurance, Surety Bonds, Factoring — all driven by a unique data patrimony, cutting-edge technology, innovation and a deep understanding of the global economy.
Joining Coface means being part of a close-knit international organization, where your ideas matter. We foster a culture of learning, collaboration and inclusion where you are given responsibilities and can see the impact of your actions.
Shape the future of trade with us. Join our Happeners!
Job DescriptionMISSION :
- You join Coface's Data Lab team and work mostly in pairs or in small teams on innovative projects.
- You design and fully develop solutions that can implement AI technologies.
- You contribute to technology watch
Ideal Candidate Profile:
- Must have a background in Computer Science
- The candidate should have 2+ yrs of experience into Data Scientist
- Hands-on experience in Machine Learning and Natural Language Processing (NLP)
- Strong Python development skills, with a focus on writing high-quality, maintainable code.
- Familiar with code reviews and continuous integration (CI) best practices.
- Experience with Docker and Kubernetes for containerization and orchestration.
- Exposure to cloud-based applications and deployment workflows.
- Proficient in SQL and NoSQL databases, including document and graph-based systems.
- Comfortable working in Linux environments and using Git for version control.
- Demonstrates autonomy, curiosity, and rigor in problem-solving and development.
About role:
The use cases for data science are varied and lead to concrete implementations. Here are some examples:
- Score the risk of corporate failure in every country
- Extract information from images, documents and web scrapping
- Build knowledge graphs from corporates linkages
- Specialize search engine and language models in identifying companies
- Generate visual and textual explanations for AI model predictions
MAIN RESPONSIBILITIES:
- The Data Lab brings together Data Science and Software engineering skills to develop and deploy solutions that improve the company's processes, products and services.
- The team seeks to make use of AI and data science techniques and to implement development best practices to deploy applications and APIs on Docker/Kubernetes infrastructures, in Apache Airflow and in the Cloud.
- Sharing knowledge through presentations between team members, training and technology watch on dedicated time are all part of the Data Lab's culture.
- Bachelor’s or master’s degree in computer science ,academic background in Data Science: supervised and unsupervised machine learning, natural language processing
- 2+ relevant experience in Data Scientist
- 0 to 3 years' experience in Python application development with high quality standards and implementation of code reviews and continuous integration best practices.
- Experience of Docker/Kubernetes deployment and cloud applications desirable
- Use of Linux and Git
- Practice of SQL and experience with NoSQL databases (document, graph)
- Autonomy, curiosity, rigor
- Flexible working model after the 1st month
- Great place to work: central and modern office
- Opportunities to learn: budget every year for training, languages platform, e-learning platform, dedicated development program…
- Career opportunities: Opportunity to build your career (both locally and internationally) in a large global company, one of the world leaders in its field
- Health care
Top Skills
Apache Airflow
Cloud
Docker
Git
Kubernetes
Linux
Machine Learning
Natural Language Processing
NoSQL
Python
SQL
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