Senior Data Scientist

Accountabilities: Develop, enhance, and optimize machine learning models by introducing new features, tuning parameters, and incorporating additional data sources. Collaborate with Machine Learning Engineers to research, develop, and deploy scalable supervised and unsupervised learning algorithms. Explore new and existing data sources to identify opportunities for improving model performance and creating new data-driven solutions. Research and evaluate innovative machine learning approaches that can optimize different stages of the product and advertising value chain. Design, run, and analyze A/B tests to validate hypotheses, measure impact, and continuously improve models and strategies. Develop solutions capable of handling sparse, high-volume datasets for use cases such as prediction, clustering, and outlier detection. Contribute to neural-network-based products supporting classification, regression, and multi-task learning. Build clean, reproducible, and well-tested code that can reliably move from research environments into production. Develop and improve monitoring tools and dashboards to track model and system performance. Work collaboratively with analysts, engineers, and other data scientists to translate business and product challenges into practical machine learning solutions. Apply an experimentation-driven, impact-focused approach, prioritizing simple and effective solutions over unnecessary complexity. Requirements: At least 5 years of professional experience developing data science or machine learning products, from initial research through production deployment. Strong programming skills and a commitment to writing clean, maintainable, reproducible, and well-tested code. Strong hands-on experience with Python, Spark, Hadoop, Airflow, Docker, and SQL. Proven experience working with algorithms designed for sparse and large-scale datasets, including prediction, clustering, and outlier detection. Practical experience developing neural network-based solutions for classification, regression, multi-task learning, or related applications is highly valuable. Knowledge of reinforcement learning and large-scale optimization is a significant advantage. Good understanding of SQL and dashboards for developing, monitoring, and improving data science and machine learning systems. Strong communication and collaboration skills, with the ability to work effectively alongside data scientists, analysts, and engineering teams. A pragmatic, experimentation-oriented mindset and the ability to focus machine learning work on measurable product and business outcomes. Previous professional experience in AdTech is required , ideally including exposure to mobile app advertising technology. Benefits: Direct collaboration with founders and the opportunity to make a meaningful impact on products and business direction. Strong opportunities for career development, learning, and professional growth. The chance to work alongside experienced industry specialists and entrepreneurs in a rapidly evolving technology sector. A diverse, multinational, and distributed team working across Europe, North America, Asia, and other regions. Flexible work-from-home arrangements. Opportunity to relocate to an international office in Berlin. $500 home-office setup budget. $1,000 annual learning and development budget.