Data Science Manager

team.5 million SMB customers with everything they need to succeed online by offering best-in-class expertise and services.
team.blue's brands are a mix of traditional hosting businesses that offer services from domain names, email, shared hosting, e-commerce, and server hosting solutions and, as specialist SaaS providers, adjacent products such as compliance, marketing tools, and team collaboration products. This broad product offering makes it a one-stop partner for online businesses and entrepreneurs across Europe.
The Head of AI & Data Platform is a senior leader within the AI & Data function, responsible for overseeing the design, development, and operation of the enterprise-wide data and AI platform infrastructure and tooling. The role ensures that the technology foundation across data and AI domains is robust, scalable, and fit-for-purpose to support strategic business outcomes.
Data & Analytics Engineering : builds and integrates data sources and pipelines.

• Data Platform Operations : owns and maintains the data platform and associated infrastructure.
• Define and execute the integrated platform strategy for AI & Data, aligned with business and technology objectives.

Serve as a key advisor to the Chief AI & Data Officer on platform and infrastructure matters.
Data & AI Infrastructure Enablement
Oversee the architecture and delivery of a modern AI & data platform, including ingestion, transformation, storage, and access layers.
Ensure compliance with data governance, security, and regulatory requirements across all platform components.
Partner closely with AI/ML, data science, product, enterprise architecture, and IT teams to ensure platforms meet cross-functional needs.
Team Development
Build and retain a high-performing team across the three sub-domains.
8+ years of experience in AI/ML or Data Engineering, with 4+ years in a leadership role managing and guiding a team of data and/or ML engineers

• Proven track record building and scaling enterprise-grade data and AI platforms.
• Strong experience in cloud-native architectures (AWS, GCP, Azure).
• Deep knowledge of modern data architectures (lakehouse, data mesh).
• Hands-on experience with data engineering, MLOps (e.g., Capable of leading cross-functional teams and defining and aligning platform vision and strategy with business goals.
• Strong communicator, able to influence senior stakeholders and drive adoption.
• At team.Check it out here .

"