Chief Data Officer

About the role

Sparteo, an AI-powered advertising technology company, is looking for a Chief Data Officer to lead its Data & AI function alongside the CTO. The role is strategic and scientific: it structures the Data department, defines the AI roadmap and unifies KPIs and dashboards across the group, while supporting sales and customer success teams.

Key responsibilities

• Restructure the Data department and define the organizational pillars (heads/leads per area).
• Define and run the AI strategy, including LLMs and agentic AI for yield optimization and internal processes, and conversational analytics for clients (RAG, text-to-API).
• Establish a single source of truth: one set of KPI definitions, formulas and naming across the group.
• Own data governance and compliance, including GDPR with the DPO, data retention and minimisation.
• Move knowledge from oral to written processes and manage the Data & AI annual budget.
• Represent Data and AI to the board, investors and partners, and lead the heads of each pillar.
• Data Engineering: own the data stack (ClickHouse, SQLMesh, Lightdash, Kubernetes) and the internal data warehouse and APIs.
• Data Science: drive yield management, bidding optimization and audience scoring, and oversee MLOps, auto-tuning and A/B testing.
• Data Analytics & BI: turn data into growth levers for Sales and CSM, own KPI access rights and guarantee dashboard accuracy.

Required profile

• Master's or Ph.D. in Mathematics, Statistics or Computer Science.
• Proven experience as a CDO or VP Data managing engineering, science and analytics teams.
• Strong mathematical and engineering background, able to challenge senior data scientists and engineers.
• Experience scaling data and ML infrastructure under tight cost discipline, ideally on bare metal and Kubernetes.
• Ability to write POCs and pair-program with the team.

Required skills

• Machine learning, from model design to real-time inference; a plus: deep learning, transformers and GPU training.
• Columnar databases and big data pipelines.
• Building custom tools and plugins with LLM assistants (Claude, OpenAI or Gemini).
• Adtech and high-frequency data environments.