Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture. In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. ## **You will be:** - designing, training, and evaluating models for bidding, forecasting, targeting, and outcome optimization across our streaming and CTV advertising platform, - designing and analyzing A/B tests and online experiments; connecting model performance to revenue and advertiser results, not just offline metrics, - turning raw campaign, audience, and supply data into robust, reusable features - and helping define them once in a shared feature store instead of rebuilding them per project, - collaborating with MLOps and Data Engineering teams to get models into production on Vertex AI and staying accountable for how they perform once live, - working with product owners and business stakeholders to frame problems, size opportunities, and translate model behavior into plain language. ## **Your profile:** - experience in applying machine learning to real products, with a track record of models that shipped and made a measurable difference, - strong Python and SQL skills, with fluency in the modern ML stack (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow), - solid grounding in statistics and experimentation - you can design an A/B test, reason about bias and variance, and know when a result is meaningful, - experience with large-scale data and cloud ML tooling; Google Cloud and Vertex AI experience are strong advantages, - clear communication skills - you can explain a model to an engineer and its impact to an executive. **Work from the European Union region and a work permit are required.** ## **Nice to have:** - background in adtech, real-time bidding, recommender systems, or marketing/measurement science, - experience with feature stores, MLOps pipelines, or moving from ad-hoc notebooks to reproducible workflows. ## **Recruitment Process:** **CV** review – **HR** call – **Interview** – **Client** Interview – **Decision**