Data Scientists / ML Engineers

Coface France
Canton of Colombes-1, France
14 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English, French
Experience level
Junior

Job location

Remote
Canton of Colombes-1, France

Tech stack

API
Airflow
Code Review
Databases
Continuous Integration
Data Mining
Linux
Python
Machine Learning
Software Engineering
Large Language Models
GIT
Kubernetes
Search Engines
Docker

Job description

of Machine Learning and AI technologies. For example: Scoring the risk of business failure with Machine Learning models Extracting information from images and documents with Transformers and LLMs Identifying companies with a custom search engine using embeddings Building and mining knowledge graphs Financial modeling and simulations The Data Lab's work includes solid Software Engineering practices to achieve operational integrations in internal tools and client applications. Data Lab's developments also include data extractions from the company's databases and management of CI/CD pipelines to deploy applications and APIs on Docker/Kubernetes infrastructures, Apache Airflow, and in the cloud. Knowledge sharing through presentations between team members, training, and technology monitoring during dedicated time are all part of how the Data Lab operates. Your missions: You join Data Lab team and most often work in pairs or small teams on innovative projects. You design and develop complete

Requirements

solutions, from data extraction and modeling to deployment on our container infrastructures or in the cloud, and monitoring in production You contribute to technology monitoring and knowledge sharing within the team Qualifications The profiles we are looking for: Engineering degree or equivalent in Data Science 3 years of experience demostrating proficiency in Python and best practices for code review and continuous integration Use of Linux and Git Autonomy, curiosity, rigor English and French are mandatory: interactions with business teams all around the world Recruitment process: Technical interview (video), including a review of the candidate's professional background - estimated duration: 1 hour Technical assessment in Python and Machine Learning, without AI coding assistance - two Colab notebooks, approximately 45 minutes each Interview with the human resources department - estimated duration: 45 minutes Job offer Additional Information Hybrid position Remote Work Benefits All our employees benefit from 3 days of remote work per week and a maximum monthly subsidy of €30. Employees receive vouchers worth €12 for each day of remote work. Language Training Depending on the type of employment contract, Coface provides employees with access to an e-learning platform dedicated to learning 6 foreign languages. Remote Work Equipment An equipment allowance of €350 for remote work is available to employees, depending on the type of employment contract. Electric Bike Purchase A contribution towards the purchase of an electric bike is available to employees, depending on the type of employment contract.

About the company

Company Description Coface DataLab is recruiting junior and senior data scientists/ ML engineers to develop and deliver operational AI/ machine learning solutions for the company. With a presence in around 100 countries, Coface is a leading global player in credit insurance and risk management. Coface is also a recognized expert in business information, surety bonds, political risk, debt collection, and factoring. We help our clients secure their business activities to build more successful companies. Directly sponsored by several members of the Group Executive Committee, the Data Lab brings together expertise in Data Science and Software Engineering to design, develop, and deploy operational solutions that improve the company's risk management, business processes, products and services. The steadily growing team now has around 30 members, mainly based in Paris, as well as in Toronto and Casablanca. Job Description The team addresses many use cases for Data Science, involving a variety

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