Data Scientist Manager

Artefactjobs·9th arrondissement of Paris, 75009, Parissenior

In short

→Liderar proyectos de IA desde el planteamiento hasta la producción con clientes de alto impacto.
→Gestionar y desarrollar un equipo de científicos de datos, fomentando su crecimiento y bienestar.
→Destacar como referente técnico y consultor para C-level, combinando rigor técnico y comunicación clara.

Fluent English required for client and team collaboration.

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What they ask for

✓Experiencia comprobada liderando proyectos de IA en entornos empresariales.
✓Capacidad demostrada para gestionar equipos técnicos y desarrollar talento.
✓Dominio técnico en machine learning, MLOps y arquitecturas de datos escalables.
✓Habilidades excepcionales de comunicación con stakeholders de alto nivel.
✓Experiencia en el diseño de soluciones de IA con impacto medible en negocio.
✓Capacidad de innovar y escalar soluciones mediante herramientas reutilizables.

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Who should you write to at Artefactjobs?

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Who we are Artefact is a French consulting and engineering firm specializing in data and AI, and a leader in Europe. Headquartered in Paris, we are now present in 23 countries across all continents, with a team of 1,700 employees. Our mission is to help businesses unlock the full potential of AI and data by developing tailor-made solutions that address their specific industry challenges. As pioneers in this field, we combine technological expertise with operational excellence, working alongside the world’s leading market players. Our clients span all key economic sectors - industry, retail, luxury, consumer goods, healthcare, and finance - and include major international corporations. Beyond consulting, we are deeply committed to making AI ethical and accessible. We launched the Artefact School of Data to facilitate career transitions into tech roles and established AI Research Centers in Paris and Shanghai. What you will be doing - Key responsibilities As a Manager Data Scientist, you will play a central role in the design, delivery and scaling of AI projects for our clients. Reporting to the CTO, your responsibilities will include: • Leading end-to-end client projects: from framing use cases with business stakeholders to implementing AI solutions that generate measurable impact. • Ensuring technical excellence: promote software engineering and MLOps best practices to deliver scalable solutions and bring them into production. • Supporting solution design: challenging business requirements, validating data availability, and selecting the most appropriate methodologies and architectures. • Being the technical reference for clients: explaining AI approaches in simple terms, providing recommendations on feasibility, risks, and ROI. • Developing trusted client relationships: interacting with C-level and operational teams to position Artefact as a long-term partner on their Data & AI journey. Beyond these core responsibilities, you will also be involved in: Managing the country’s data science team • Support team staffing, ensuring the right skills are applied to meet project needs. • Ensure each individual’s continuous well-being within the team, supporting their growth through mentoring, coaching, and career development plans. • Help define the team’s career framework and participate in performance review processes. • Challenge existing ways of working and drive innovation to continuously improve Artefact’s data science team. Developing Artefact’s technical expertise • Contribute to testing and implementing advanced AI approaches and emerging techniques on client use cases. • Drive initiatives to build internal accelerators, such as modules and tools that can be reused across projects. • Maintain an active technology watch: evaluate emerging tools, frameworks, and cloud services to assess how they can address client needs. • Share knowledge through workshops, informal training sessions, and documentation, fostering a culture of continuous learning. Being a great tech manager • Lead by example: demonstrate technical rigor, pragmatic problem-solving, and the ability to step in directly on projects when the team needs support. • Provide constructive feedback to help data scientists in your team progress in both technical and consulting dimensions. • Anticipate risks and unblock teams, ensuring projects stay on track. • Balance ambition and feasibility: critically assess approaches, driving innovation while ensuring solutions stay realistic to deliver. • Foster collaboration between data scientists, data engineers, and business teams to en

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