Senior Data Scientist

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. The company specializes in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, and others. They work with technologies including AWS, Azure, GCP, Databricks, and Snowflake.

• Extensive hands-on experience in designing, training, and improving Deep Learning models for business-critical production use cases
• Proven expertise in deep learning frameworks such as PyTorch or TensorFlow, and strong practical knowledge of Pandas and NumPy
• Advanced SQL skills, preferably including analytical SQL for large-scale data environments
• Strong experience with public cloud infrastructure, preferably Google Cloud Platform, including ML-oriented services such as Vertex AI and Vertex Pipelines
• Proven ability to lead end-to-end model development, from problem framing and feature design to evaluation and production handoff
• Strong engineering foundations, including writing production-level, testable, and documented Python code, with familiarity with CI/CD practices
• Ability to mentor other Data Scientists and raise modeling standards across the team
• Relevant academic degree or extensive professional experience in a STEM field (e.g., Computer Science, Mathematics, Mathematical Statistics, Quantitative Methods, or Physics)
• Openness to on-site workshops 1-3 times per quarter in Warsaw

Nice to have:

• Experience in developing ML models for low-latency online applications
• Experience within the advertising or marketing domains
• Demonstrated experience in developing ML models for predicting business events like clicks or conversions (CTR and CVR modelling)
• Proficiency in traditional machine learning techniques, such as Gradient Boosted Trees
• Experience in mentoring, technical leadership, or coordinating model development across a broader team
• Practical use of AI-assisted coding tools to improve engineering productivity and quality

• Drive the design, refinement, and evaluation of ML scoring models (e.g., CTR, CVR, and RoAS) integral to core bidding logic
• Design architecture of model strategies integrating user, product, and placement signals for high-throughput and low-latency environments
• Collaborate with engineering and business stakeholders to translate strategic goals into measurable modeling outcomes and technical roadmaps
• Provide technical leadership and quality assurance for Data Science workstreams within the project scope to ensure alignment with production standards

Work from the European Union region and a work permit are required.