Data Scientist - Entry Level

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. Your mission   We're seeking a passionate and energetic Junior Data Scientist to join the Data CRT (Community Relation Team), and help us build the intelligent systems that enable our amazing agents to support the millions of BlaBlaCar members out there. Your mission will be to: • 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.   Your responsibilities   • 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.   Your qualifications   • 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   What we have to offer   • 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   Interested in joining the ride?   • 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