Chief Data Officer

OpenKrill; United States; A distancia; USD 180.000 - 320.000; Jornada completa

Descripción de la vacante

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.

Formación

• 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

Responsabilidades

• 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.

Conocimientos

Adtech

High-Frequency

Data architecture

AI mastery

AI tooling

Hands-on auditing

MS/PhD

Educación

Master’s or PhD in Mathematics/Statistics/CS

Herramientas

Kubernetes

Columnar databases

Descripción del empleo

Sparteo is an independent suite of AI-powered advertising technologies built on sustainable, sovereign infrastructure.

Since 2018, we’ve been reshaping programmatic advertising to make it faster, more transparent, and more profitable by building the most direct path between publishers and advertisers.But we don’t stop here: wherever attention lives, on the web, in apps, on CTV, and beyond, our mission is to monetize audiences, across every device. Our data-driven tech delivers 30% higher revenues for our clients on average than traditional solutions. Our Solutions:

• Actirise: the display tech designed for performance
• FastCMP: the consent management platform specifically designed for business purposes
• Meetscale: the most advanced SSP for Publishers and Ad Networks
• Viously: the ultimate all-in-one video tech solution

Behind Sparteo’s growth is a team of 100+ talents across 11 countries, united by a shared ambition to redefine the future of digital advertising. Our dedication has placed Sparteo among the most dynamic tech players in Europe:

• FT1000 ranking: Among the fastest-growing European companies in 2024 & 2025
• The Europas: Featured in the list of 100 hottest startups
• Pixalate Ranking: #1 Web SSP in France with our Actirise solution, overtaking Google AdExchange

These milestones are just the result. What truly sets us apart is how we work: at Sparteo, we don’t settle, we act.

• We are Drivers, not passengers: We take the wheel and own our results.
• We are data-obsessed: Facts guide us, not assumptions, not egos.
• We think as one: Collective goals come before personal wins.
• We trade off: We simplify, prioritize, and go for high-impact results.
• We solve problems: We own challenges and turn ideas into action.
• We say what we do: Radical transparency is how we grow, no fluff, no hiding.

Discover our journey, products, and culture on our website: https://corporate.sparteo.com/

The Challenge: Driving Intelligence for a Scalable Adtech

Our client-facing products and real-time analytics are best in class. The first mission is to bring the same level to our internal teams (Sales, CSM): internal data APIs, unified dashboards and one shared set of KPI definitions.

The CDO leads the entire Data & AI function and works hand in hand with the CTO. This is not an administrative role, but that of a leader with strong scientific and mathematical authority, able to understand and challenge the work of senior data scientists and engineers, and to support them on the toughest problems. The goal is not to out-code the team but to structure it, set direction and act as a mirror. You will orchestrate the synergy between infrastructure, Artificial Intelligence (including Generative AI) and Business Intelligence.

Strategic Objectives & Vision

• Restructuring: Structure the Data department to support Sparteo’s growth.
• “Architect” Vision: Define the organizational building blocks (Heads/Leads per pillar) to elevate global technical maturity.
• AI Roadmap: Define and execute the strategy for integrating LLMs and Agentic AI to automate yield optimization and internal processes, including our internal data agent and conversational analytics for clients (RAG, text-to-API).
• Single source of truth: One set of KPI definitions, formulas and naming across the group.
• Data governance & compliance: Own data governance across the group, including GDPR compliance in partnership with our DPO, data retention and minimisation.
• Documentation & knowledge management: Help a strong team move from largely oral knowledge to written, durable processes.
• Budget ownership: Manage the Data & AI annual budget and decide where to automate and where to hire.
• Representation: Carry the voice of Data and AI to the board, investors and external partners.
• Holistic Management: Lead the Heads/Leads of each pillar to ensure total coherence of the Data/AI value chain.

The Three Pillars Under Your Direction

1. Data Engineering & AI Infrastructure (The Real-Time Backbone)

• High-Performance Infrastructure: Validate technological choices to absorb massive volumes of ad-requests with minimal latency, on self-operated, lean infrastructure under tight cost discipline.
• Production Pipelines: Ensure the availability of critical data flows for bidding and monetization and real-time AI inference.
• Standardization & Stack: Own the data stack (ClickHouse, SQLMesh, Lightdash, Kubernetes on bare-metal infrastructure operated in-house) and CI/CD processes for seamless scalability.
• Internal data platform: Own the evolution of our data warehouse, expose internal data APIs with proper access controls, and make sure our internal data agent queries the warehouse rather than raw data.
• Cross-functional steering: Co-lead with the CTO the weekly review on infrastructure, pipelines, AI and resource consumption.

2. Data Science (The Algorithmic Heart & MLOps)

• Algo Wars & Yield: Drive innovation in yield management, floor pricing, throttling, bidding optimization (including bandit approaches) and audience scoring via advanced predictive models and reinforcement learning.
• Scientific Credibility: Possess a “high-level” mathematical background to guide the team (3 people).
• ML Lifecycle (MLOps): Validate strategies for auto-tuning, versioning and A/B testing of algorithms within a constrained production environment, including experimentation designs where classic A/B testing reaches its limits.
• Team structuring: Structure the team’s roadmap, objectives and follow-up, and bring fresh perspectives to strong, autonomous experts.
• Audit: Audit mathematical models and maintain a standard of excellence.

3. Data Analytics & BI (The Business Engine)

• Insights Strategy: Transform raw data and AI-generated insights into growth levers and revenue strategies for Sales and CSM teams.
• Data product approach: Data contracts, versioning and internal APIs feeding dashboards and agents.
• Access rights: Own the KPI access-rights policy with business owners, each business line remaining owner of its data.
• Scale through automation: Scale analytics through the internal data agent rather than headcount.
• Partnership: Act as a privileged point of contact for executive management and investors.
• High-Fidelity Reporting: Guarantee the accuracy of dashboards (supervision of one person).

Your profile for this jobTechnical Expertise & Real-Time DNA

• Adtech / High-Frequency DNA: Experience in very high-volume environments (High-Frequency Trading, Adtech) is crucial for mastering real-time prediction challenges.
• Lived scaling experience: Has personally scaled and optimized data and ML infrastructure under tight cost discipline, ideally bare metal and Kubernetes, not only in elastic cloud environments.
• Data architect: Able to own architecture decisions end to end.
• AI Mastery: Strong expertise in Machine Learning, from model design to real-time inference, with hands‑on experience building continuous learning pipelines that keep models accurate and reliable at scale. A plus: deep understanding of Deep Learning, Transformers and GPU-based training and inference.
• Advanced AI tooling (mandatory): Builds own skills, plugins and artifacts with LLM assistants (Claude at Sparteo; OpenAI or Gemini equivalents accepted).
• “Hands‑on” Expertise: Proven ability to audit code, validate data architectures on self-operated infrastructure and master columnar databases and big data pipelines.
• Academic Excellence: Master’s or Ph.D. in Mathematics, Statistics or Computer Science.

Leadership & Management

• Technical Authority: Engineering, AI and mathematics level “much higher” than the average manager in the sector.
• Proven Experience: Confirmed experience as a CDO or VP Data managing multidisciplinary teams (Eng + Science + Analytics).
• Leads from the front: Writes POCs, pair-programs, lives the problems with the team rather than delegating from afar.
• Culture: Direct, tr