Hermès Data Technical Manager
- Location
- ParisÎle-de-FranceFrance
- Employment
- Full-Time
- Seniority
- Manager
- Department
- IT & Technology Systems
- Posted
- Aug 18, 2026
About Hermès
This prestigious fashion house, renowned for its timeless elegance and innovative designs, is a part of a leading global luxury conglomerate. The brand is committed to excellence and offers a dynamic environment where creativity and business acumen are equally valued.
Hermès Digital seeks Data Technical Manager in Paris to lead Data/ML teams driving AI innovation across 33 global e-commerce platforms. Leadership, technical excellence, MLOps expertise required.
Role & Responsibilities
- Define and champion the technical vision for Data, ML, and AI within the Digital, Sales & Services division (HDVS)
- Identify architectural constraints, design technical solutions in collaboration with architects, and ensure system coherence, performance, and scalability
- Establish and uphold code quality standards, best practices (TDD, CI/CD, MLOps, DataOps), and data security protocols across the team
- Lead and mentor a mixed team of Data Scientists and Data Engineers, fostering autonomy, accountability, and collective excellence
- Facilitate knowledge transfer through mob programming, pair programming sessions, mentoring, and encouragement of conference attendance and meetup participation
- Drive project delivery from exploration through production, ensuring timely completion and quality standards for Data and AI initiatives
- Supervise production system stability and performance through monitoring, alerting, and incident management; pilot continuous improvement actions
- Collaborate closely with business teams (Product, eRetail, Finance, HR, CRM) to translate complex business challenges into data-driven solutions
- Communicate technical concepts to non-technical stakeholders and foster a data-driven culture across the organization
- Actively participate in recruitment and onboarding of team members
- Anticipate and mitigate technical, organizational, and ethical risks, including bias, GDPR compliance, and data security
Qualifications
- Engineer's degree or Master's 2 in Data Science, Computer Science, Statistics, Applied Mathematics, or equivalent
- Minimum 7 years of professional experience in data science, machine learning, or data engineering
- At least 2 years of experience in a technical leadership or management role within a Data/ML team
- Solid foundation in statistical modeling, machine learning (predictive, classification, time-series), and deep learning
- Strong understanding of data pipeline architectures (batch and streaming), data warehouses, and modern data lakes
- Proficiency with MLOps and DataOps practices, model deployment tools (MLflow, Kubeflow), CI/CD, monitoring, and data drift management
- Experience with generative AI, large language models (LLMs), RAG approaches, intelligent agents, and foundation model APIs (OpenAI, Hugging Face)
- Demonstrable expertise with cloud environments (AWS, GCP), Git, Docker, Kubernetes, and infrastructure-as-code tools (Terraform)
- Proven ability to unite complementary Data Science and Data Engineering profiles around ambitious shared objectives
- Strong coaching and mentoring skills with capacity for regular, constructive feedback and fostering team autonomy
- Excellent communication skills with the ability to simplify complex technical concepts for business stakeholders
- Demonstrated humility, rigor, high standards for code quality and data ethics, and commitment to continuous improvement
Skills
Experience
Minimum 7 years of professional experience in data science, machine learning, or data engineering, with at least 2 years in a technical leadership or management capacity within a Data or ML team. Demonstrated track record of leading cross-functional teams, deploying production machine learning systems, and collaborating with business stakeholders to drive data-driven transformation.
Education
Engineer's degree or Master's 2 in Data Science, Computer Science, Statistics, Applied Mathematics, or equivalent qualification.
Workplace
This position is based in Paris, Île-de-France, France.
Benefits
Joining the Maison Hermès, an artisan of exceptional products; involvement in an exciting from-scratch project; membership in a quality-focused, collaborative team committed to professional development; substantial autonomy and encouragement of individual initiative.
Culture
The company fosters a collaborative and innovative culture, encouraging employees to push the boundaries of creativity while maintaining a strong commitment to sustainability and ethical practices.
About Cerulean
Cerulean is the definitive career portal for the global luxury industry. We match exceptional professionals with exclusive opportunities at the world's most prestigious brands. From haute couture and fine watchmaking to prestige beauty, hospitality, and boutique retail, Cerulean centralises luxury employment to help you find the career for which you were destined.
Frequently Asked Questions
The luxury industry is characterised by a diverse and nuanced nomenclature. Esteemed houses frequently employ proprietary terminology, and even within a single organisation like Hermès, titles may vary across global markets to reflect local conventions. To ensure absolute clarity, Cerulean assigns a standardised, industry-coherent canonical title to every listing. However, it is worth noting that this role is functionally synonymous with «Technical Lead, Data & AI», «Data Engineering Manager», «ML Platform Manager», «Data Systems Team Lead», and other variations. Our sophisticated search architecture anticipates these variations, ensuring that inquiries using related terms will seamlessly yield the exact roles you desire.