Data Scientist
Role details
Job location
Tech stack
Job description
We are seeking a VP Data Science to lead our Data Science function within Planning Agent, our AI-powered advertising planning platform used daily by agency teams. This role will shape the future of agentic AI in marketing technology, driving innovation in how planners interact with intelligent systems across optimization, allocation, and planning workflows.
While the product is moving towards agentic, our agents remain grounded in machine learning and complex mathematical models (e.g., econometrics, reach modelling). Success in this role depends on bridging the best of both worlds: machine learning models that provide structure and accuracy, and agentic systems that draw on unstructured inputs such as media briefs and contextual data. This combination allows planners to make decisions that are both reliable and informed by real-world context.
As the leader of our Data Science organization, you will oversee a team of 10+ senior data scientists distributed across Europe, guiding them in the design, implementation, and productizing of multi-agent workflows. While grounded in technical leadership, this role blends strategy and hands-on expertise: setting the data science roadmap, ensuring delivery at scale to build reliable, production-ready agents.
This is a leadership role with strong technical depth. You'll serve as both a coach and an architect of the team, shaping best practices for data science in agentic systems, while partnering closely with Engineering and Product.
Tasks & Responsibilities
- Lead and manage a distributed team of data scientists embedded in cross-functional squads across the Planning organization.
- Define and communicate the long-term Data Science roadmap for agentic AI within Planning.
- Drive the design and deployment of multi-agent workflows using orchestration frameworks such as LangGraph, ensuring scalability, reliability, and measurable business impact.
- Partner with Product, Engineering, and stakeholders to align agentic AI capabilities with planner workflows and business objectives.
- Establish best practices for experimentation, evaluation, and monitoring of agent-based systems (including causal tracing, benchmarking, and safety checks).
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Requirements
- 8+ years of experience designing and deploying applied ML or AI systems into production, with at least 3+ years leading data science teams.
- Fluent in Python and a strong interest in general software engineering principles.
- You have worked with common python frameworks (Numpy, Pandas...)
- Demonstrated expertise with agentic AI systems, including orchestration frameworks (LangGraph preferred, LangChain or similar also considered).
- Strong foundation in classical machine learning and applied modeling techniques, including regression, classification, clustering, and practical experience with models used in econometrics or marketing measurement.
- Experience with agile development methodologies, such as Scrum or Kanban.
Preferred Qualifications
- Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes).
- Familiarity with DevOps practices and tools for continuous integration and deployment.
- Solid understanding of system design principles, scalability, and performance optimization.
Benefits & conditions
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