Data Scientist

About the team: Within Global Operations, our mission is to deliver the best customer experience in the fintech industry by providing an effortless, high-quality experience for every merchant. We are looking for a skilled and passionate Data Scientist to join our AI Team, contributing to the development of customer-facing models and the evaluation of our AI products. Your work will help elevate our customer support by improving quality, identifying gaps, and tailoring the experience to merchants’ needs. As a Data Scientist at SumUp, you will design, test, and implement both traditional machine learning and AI models, while also assessing the effectiveness of our AI products. You will have a direct impact on company performance by developing and scaling evaluation methods that measure service quality across agents and AI assistants, identify opportunities for improvement, and ensure we deliver the right support experience for each merchant segment. You will collaborate closely with cross-functional partners — including analysts, ML engineers, data scientists, and product managers — to translate business needs into measurable, production-ready ML solutions. Your contributions will help shape the future of our customer support experience and enable SumUp to grow sustainably with a strong customer-first focus. What you’ll do Build and improve LLM-based evaluation models (LLM-as-a-Judge) to assess the quality, safety, and effectiveness of AI products (e.g., AI assistant outputs, agent copilots, support automation). Help design and implement automated QA and evaluation pipelines that enable continuous monitoring and benchmarking of AI product performance at scale. Contribute to end-to-end model development, from problem framing and data exploration to deployment and monitoring, with guidance and support from the team. Own the forecasting models and work with WFM to improve the accuracy. Develop and maintain data pipelines that combine product signals, customer support interactions, and feedback loops to support reliable evaluations and insights. Support the creation of qualitative and quantitative observability frameworks, including rubrics, evaluation criteria, labeling strategies, and error categories to understand model performance and failure modes. Produce actionable insights from evaluation outputs to identify gaps and improvement opportunities, and communicate recommendations to product and operations stakeholders. Build and iterate on ML models (AI or traditional) that improve support efficiency, such as prediction models for routing, deflection, resolution likelihood, or quality scoring. Collaborate closely with data scientists, analysts, ML engineers, and product managers to deliver measurable improvements to customer support experiences. Learn and share best practices across the data and AI community at SumUp, contributing to a culture of continuous improvement. You’ll be great for this position if you have: 3+ years of experience applying data science to real-world products, ideally in AI systems, customer support, quality measurement, or evaluation frameworks. Solid understanding of machine learning and statistics, including experimentation and metric design. Experience working with LLMs or NLP systems, and interest in evaluation methods (e.g., rubric-based scoring, prompt-based judges, calibration approaches, or human-in-the-loop evaluation). Strong ability to write clean, reliable code in Python (pandas, numpy, scikit-learn) and strong working knowledge of SQL. Experience building or contributing to data workflows and pipelines, and familiarity with taking models into production environments. Confidence communicating results and insights to both technical and non-technical stakeholders, with a strong focus on practical business impact. A proactive mindset and willingness to take ownership of tasks while collaborating closely with the team in a fast-paced setting. Why you should join SumUp: Oppo ... (truncated, view full listing at source)