About BlaBlaCar

BlaBlaCar is the world’s leading community-based travel app enabling 27 million members a year to carpool or travel by bus in 21 countries. Our team of 800 employees counts over 50 nationalities and is spread across our 5 global offices, 30% working fully remotely.

• Shape the future of the CR ecosystem: Develop and deploy cutting-edge machine learning models that optimize the processes, ensuring our members will always feel listened to and receive quickly the best support for their needs.

• Enhance platform trust & efficiency: Build intelligent automation solutions, from real-time fraud detection and AI-powered content moderation (text, images) to leveraging generative AI for automated translation and improved customer support.

• Empower data-driven decisions: Create impactful data products and applications that provide actionable insights, directly influencing BlaBlaCar's commercial success.

• Pioneer with generative AI: Explore and implement innovative generative AI use-cases to boost internal efficiency, automate operational tasks, and democratize data access across the company.

• Develop & deploy ML models: Design, build, and ship machine learning models into production, collaborating closely with other Data Scientists and ML Engineers to directly enhance our core marketplace (e.g., matching, ETA).

• Implement automation of internal capabilities: Implement intelligent solutions for real-time fraud detection, utilize deep learning for profile picture moderation, and leverage LLMs for text moderation and generative AI for tasks like translation.

• Contribute to generative AI innovation: Actively identify, prototype, and implement generative AI solutions to enhance employee productivity and automate key operational processes.

• Grow in your role: Be ready to be mentored and learn, and bring energy and novel point of view to the team.

• Collaborate across a 360° data team: Work within our autonomous data team, comprising ML Engineers, Data Analysts, Data Engineers, and fellow Data Scientists, managing projects end-to-end.

• At least 1 year of professional experience in data or software engineering, with an experience putting Machine Learning models in production or producing data-based applications.

• Knowledge of Machine Learning theory, statistics and probabilities and/or econometrics modeling is required.

• Fluency in SQL and Python. Knowledge of main machine learning packages (scikit, XGBoost, etc) and/or MLOPs frameworks (KubeFlow, Tensor FLow, Vertex AI, etc) are a plus. Experience with python data visualization apps (Streamlit, Flask, Dash, etc) is also a plus.

• Excellent communication skills: You are able to explain your models clearly to both analysts and decision makers.

• Pragmatic approach to problems: You can design intermediate solutions in an agile environment, and put them in production.

• Strong business sense: You like to partner with business managers to propose new strategies and validate their hypotheses through data.

• Fluent in English

• Hybrid status for this role : 2-3 days at the Office

• 4 additional weeks on top of legal maternity/paternity leaves

• 50% healthcare coverage (Alan)

• Financial support for home office equipment

• Minimum 25 days holiday per year

• Local meal plan policy (Swile card)

• 50% transportation paid (Forfait Mobilité Durable)

• Free unlimited carpooling & bus rides

• Personal growth via trainings, mentorship, and internal mobility programs

• Employee Stock ownership plan

• Regular team building events

• 1 day off per year to test our product

• 1 day per year for social engagements with non-profits

• a 45-min video-call with Maxime Gaudilliere, Talent Acquisition Manager, to get to know you, understand your career expectations and answer your questions

• a 45-min video-call with Fabio Cecchi, Engineering Manager, Engineering Manager, to discuss your experience and share more details about the team

• a 90-min technical assessment with the Data Science Chapter Lead and a Software Engineer

• a 30-min interview with Orianne Friedrich, Head of Data