Data Scientist

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Scientist based in Switzerland. As a Data Scientist, you’ll work on machine-learning models that process terabytes of data and support billions of real-time advertising requests and users worldwide. You’ll contribute across the full data science lifecycle, from research and data exploration through experimentation, model development, and production deployment. Working closely with machine learning engineers, analysts, and other data scientists, you’ll develop scalable solutions that improve product performance and deliver measurable business outcomes. You’ll continuously enhance existing models by introducing new features, optimizing parameters, and identifying valuable data sources. The role offers significant scope for experimentation, including A/B testing, algorithm research, and exploration of advanced machine-learning techniques. You’ll join a diverse, globally distributed team working in a fast-paced environment where simplicity, collaboration, and practical impact are highly valued. This is an opportunity to work on complex, large-scale machine-learning challenges while helping shape the future of programmatic advertising. Accountabilities - Develop, improve, and maintain data science products throughout the full lifecycle, from initial research and experimentation through production deployment. - Continuously enhance existing machine-learning models by incorporating new features, fine-tuning parameters, and leveraging additional data. - Collaborate closely with Machine Learning Engineering teams to design and deploy scalable supervised and unsupervised learning algorithms. - Explore new and existing data sources to identify opportunities for improving model performance and generating additional insights. - Research and evaluate new machine-learning approaches that can optimize different stages of the product and advertising value chain. - Design, run, and evaluate A/B tests to validate hypotheses, measure impact, and guide product and modeling decisions.

- Apply algorithms to sparse and large-scale datasets for use cases including prediction, clustering, and outlier detection. - Build and improve monitoring dashboards and SQL-based tools to track model and product performance. - Write clean, reproducible, well-tested code and contribute to reliable, maintainable data science workflows. - Work collaboratively with data scientists, analysts, engineers, and other stakeholders to translate complex problems into practical, scalable solutions. - Maintain a strong focus on business and product impact, ensuring machine-learning initiatives deliver measurable value for customers and the wider business. Requirements: - At least 3 years of relevant experience developing data science products, ideally covering the complete journey from research and experimentation to production deployment. - Strong programming skills, with a focus on writing clean, reproducible, maintainable, and well-tested code. - Strong proficiency in Python, Spark, Hadoop, Airflow, Docker, and SQL. - Hands-on experience working with algorithms designed for sparse and large-scale datasets, including prediction, clustering, and outlier detection. - Good understanding of data analysis, experimentation, and statistical evaluation, including experience designing or interpreting A/B tests. - Previous experience in Ad-Tech is required. - Experience using Gradient Boosting Trees such as CatBoost or LightGBM in production environments is a plus. - Experience developing neural-network-based products for classification, regression, or multi-task learning is highly valuable. - Knowledge of reinforcement learning and large-scale optimization problems is a significant advantage. - Good understanding of dashboards and SQL-based monitoring solutions.