In this role you will lead advanced analytics and AI-driven solutions within a cross-functional Data Science team. You’ll design and deploy ML models at scale to impact multiple business areas in travel, from personalization to optimization, contributing to eDO’s mission to become a general leader in online travel. You’ll mentor peers, engage with stakeholders, and stay at the forefront of ML/AI advances to drive value. This hybrid role offers a hands-on, impact-focused environment with a strong emphasis on practical ML solutions and innovation.
Compensaciones / Beneficios
- compensation package
- Prime Plus membership and benefits
- flexible benefits
- birthday day off
- Coursera access and learning programs
- onboarding program
Responsabilidades
- Drive value and growth with multidisciplinary teams and stakeholders
- Own initiatives from inception to delivery
- Provide transparency on progress to team and stakeholders
- Influence decision-making with best-practice ML guidance
- Stay updated on advances in machine learning and AI
- Lead and mentor data scientists
- Advocate for machine learning and AI within the organization
- Uphold company values and foster a collaborative environment
Requisitos principales
- Degree in a quantitative field
- 5+ years in data science, AI, or ML engineering
- Solid understanding of statistical methods and ML techniques with open-source frameworks
- Production-ready ML solutions and MLOps experience
- Experienced Python developer; other languages a plus
- Cloud platforms and scalable solution experience
- Generative AI experience with LLMs and LangChain a plus
- Strong written and oral English communication skills
- Proactive with disruptive thinking
- Strong communication and stakeholder management
- Leadership and mentoring abilities
- Python
- MLOps
- Cloud platforms
📌 Senior Data Scientist - (Hybrid) - barcelona
🏢 Edreams
📍 Barcelona
Postulate a este anuncio
Muestra tus habilidades a la empresa, rellenar el formulario y deja un toque personal en la carta, ayudará el reclutador en la elección del candidato.