Chief Data & AI Architect

OpenKrill; United States; Remote; USD 180,000 - 320,000; Full time

Job summary

Sparteo is seeking a CDO/VP Data to lead Data Engineering, Data Science, and Analytics with a focus on real-time AI systems, governance, and alignment with business goals. You will shape the data roadmap, own the KPI framework, and partner with CTO and board to drive growth.

The role demands strong mathematical authority, hands-on leadership, and proven experience in high-volume adtech environments, including self-operated infra and ML lifecycle management.

Qualifications

• Experience in very high-volume environments (Adtech)
• Scaled data and ML infra under cost discipline
• Owns architecture decisions end to end
• Hands-on ML with real-time inference and continuous learning pipelines
• Proven ability to audit code and validate data architectures

Responsibilities

• Structure the Data department to support Sparteo’s growth.
• Define pillars (Data Engineering, Data Science, Data Analytics) and leaders.
• Define AI roadmap for LLMs, Agentic AI, yield optimization, and internal analytics.
• Establish a single source of truth: KPI definitions and naming conventions.
• Own data governance and GDPR compliance in partnership with DPO.
• Manage Data & AI budget and strategic hiring decisions.
• Represent Data & AI to board, investors, and external partners.
• Lead Heads/Leads to ensure coherence of the Data/AI value chain.

Skills

Adtech

High-Frequency

Data architecture

AI mastery

AI tooling

Hands-on auditing

MS/PhD

Education

Master’s or PhD in Mathematics/Statistics/CS

Tools

Kubernetes

Columnar databases

Job description

Sparteo is seeking a CDO/VP Data to lead Data Engineering, Data Science, and Analytics with a focus on real-time AI systems, governance, and alignment with business goals. You will shape the data roadmap, own the KPI framework, and partner with CTO and board to drive growth.

The role demands strong mathematical authority, hands-on leadership, and proven experience in high-volume adtech environments, including self-operated infra and ML lifecycle management.