Senior Data Scientist; Remote from Switzerland

Role Overview

This role offers the opportunity to influence the quality and effectiveness of AI models by leading the evaluation, curation, and optimization of large-scale datasets. You will design and implement statistical and machine learning methods to ensure datasets are diverse, representative, and high‑impact. Collaborating closely with research and engineering teams, you will define data quality standards, develop assessment frameworks, and create tools to automate preprocessing and validation.

This position combines hands‑on technical work with strategic guidance, allowing you to shape the future of AI model performance. Ideal candidates are independent problem‑solvers with strong analytical skills, experience with unstructured datasets, and a passion for data‑centric AI research. This is a fully remote role in a fast‑paced, collaborative, and high‑trust environment.

• Lead the evaluation, curation, and optimization of large-scale datasets used for AI model training.
• Design and apply statistical and machine learning techniques to filter, enrich, and assess data quality.
• Develop frameworks to measure data diversity, duplication, and informativeness, reducing risks in training datasets.
• Collaborate with model training teams to identify bottlenecks and optimize dataset performance.
• Provide leadership on data quality strategy and define internal best practices.
• Evaluate external datasets for integration, focusing on scalability, quality, and relevance, and develop data scorecards.
• Contribute to the research and development of tools for automated data preprocessing, validation, and enrichment.

• PhD or equivalent Master’s degree with 4+ years of industry experience in machine learning, computer science, statistics, mathematics, engineering, or a related quantitative field.
• Strong understanding of AI model training pipelines, including data preprocessing and evaluation.
• Experience with large, unstructured datasets, especially text‑based data.
• Background in statistical analysis, bias detection, and data validation.
• Proven ability to identify high‑impact problems and implement independent solutions.
• Excellent collaboration and communication skills for cross‑functional teamwork.
• Bonus: experience with synthetic data generation or augmentation, open‑source contributions, or publications in data‑centric AI, and experience developing evaluation frameworks or performance metrics.

• Competitive compensation package with performance‑based incentives.
• Fully remote and flexible working arrangements.
• Opportunity to work on high‑impact AI projects with cutting‑edge datasets.
• Collaborative, high‑trust culture emphasizing velocity, impact, and experimentation.
• Direct influence on AI model performance and data quality strategy.
• Exposure to advanced research and applied machine learning initiatives.

We appreciate your interest and wish you the best!

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