Data Scientist Manager

the Jungle; Paris; Sur place; EUR 75 000 - 95 000; Plein temps

Résumé du poste

A leading consulting and engineering firm in Paris is seeking a Senior Data Science Manager to lead client projects and manage the data science team. Candidates should have 5+ years of hands-on experience in AI and software engineering best practices. The role emphasizes team growth, collaboration, and delivering impactful solutions. A commitment to ethical AI is also essential.

Qualifications

• 5 years of hands-on experience developing data-driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience with industrializing AI workflows in cloud environments.

Responsabilités

• Lead end-to-end client projects from framing use cases to implementing AI solutions.
• Ensure technical excellence and deliver scalable solutions.
• Develop trusted client relationships interacting with C-level teams.
• Support team staffing and individual growth through mentoring.
• Foster collaboration between data scientists and business teams.

Connaissances

Applied machine learning

Generative AI

Software engineering best practices

MLOps

Stakeholder management

Problem-solving

Description du poste

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 1700 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 worlds 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.

Key responsibilities

• 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.

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 Artefacts data science team.

Developing Artefacts 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 ensure solutions are effectively integrated and adopted.

Qualifications - What we are looking for

• 5 years of hands‑on experience developing data‑driven solutions.
• Strong knowledge in applied machine learning and generative AI.
• Solid understanding of software engineering and MLOps best practices.
• Experience with industrializing AI workflows in cloud environments.

In addition to technical expertise we value individuals who can

• Lead teams manage stakeholders and deliver impactful projects in a business context.
• Show intellectual curiosity and excellent problem‑solving skills.
• Tackle challenges with pragmatism and creativity.
• Support growth mentoring juniors and constructively challenging seniors.
• Earn trust from both peers and business stakeholders.

Our recruitment process

• HR call
• Standard Interview
• Technical Interview
• Fit Interview

Equal Opportunity Statement

At Artefact we recruit our employees solely on the basis of our needs and the individual qualities of each candidate. We ensure the development of their professional skills and responsibilities without discrimination of any kind including belief gender age disability ethnic origin sexual orientation membership of a political organization religion trade union or minority group.