Staff Data Scientist

Your role in the team

Our expectations of you

Qualifications

• The ideal candidate will demonstrate:
• World-Class AI and ML Expertise:
• Deep Research Authority in ranking models and cutting-edge approaches to personalisation, relevance, and multi-objective optimisation under uncertainty.
• Expertise in bidding algorithms, reinforcement learning (RL), and the ability to invent or adapt novel ML architectures to solve previously intractable problems at massive scale.
• Deep operational knowledge of AI frameworks (e.g., TensorFlow, PyTorch) and their application in mission-critical, ultra-low-latency real-time decision systems.
• Advertising Domain Mastery & Economic Acumen:
• A comprehensive and deep-seated understanding of ad auctions, ad exchange platforms, and macro-economic dynamics within the programmatic advertising space.
• A track record of using probabilistic modelling, causal inference, and statistical rigour to validate assumptions and inform the design of new auction mechanisms and platform policies.
• Exceptional Data and Statistical Expertise:
• Advanced proficiency in Python, SQL, and designing robust, end-to-end data workflows for front-end tracking and large-scale behavioral data.
• The ability to formulate and solve the most complex multi-objective problems, effectively balancing conflicting metrics like revenue, engagement, fairness, and system stability.
• Visionary Leadership in AI Systems:
• A demonstrated track record of successfully designing, building, and deploying multiple generations of large-scale AI systems that have delivered measurable, multi-million-euro business outcomes.
• A history of mentoring Staff and Senior Staff engineers/scientists and building alignment across a diverse set of engineering, product, and data organizations to deliver on ambitious goals.
• Nice-to-Haves:
• Expertise in econometrics or game theory as applied to advanced auction and pricing strategies.
• Major Contributions to open-source AI tools or publications in top-tier machine learning conferences (e.g., NeurIPS, ICML, KDD).
• Knowledge of calibration techniques and advanced methodologies to ensure prediction and decision reliability in high-stakes environments.
• Deep familiarity with Transformer-based architectures or Graph Neural Networks for modeling complex user-item and market interactions.

Experience

• Proven experience optimizing CPC, CPA, and ROAS metrics by driving significant business outcomes across multiple product cycles.
• Experience in defining and driving the organization-wide technical strategy (2+ years outlook) for Data Science and ML, influencing the roadmaps of multiple Engineering and Product teams.