Senior Data Scientist (Remote, Denmark)

Job summary

This role focuses on enhancing the quality and effectiveness of AI models through the evaluation and optimization of large datasets. The position involves designing statistical and machine learning methods to ensure datasets are diverse and impactful, while collaborating with research and engineering teams to establish data quality standards and automate processes.

Qualifications

• PhD or equivalent Master’s degree with over 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, particularly text-based data.
• Background in statistical analysis, bias detection, and data validation.
• Proven ability to identify significant problems and implement solutions independently.
• Excellent collaboration and communication skills for cross-functional teamwork.
• Bonus: experience with synthetic data generation, open-source contributions, or publications in data-centric AI, and experience developing evaluation frameworks or performance metrics.

Responsibilities

Benefits

• Lead the evaluation, curation, and optimization of large-scale datasets for AI model training.
• Design and apply statistical and machine learning techniques to assess and enhance data quality.
• Develop frameworks to measure data diversity and informativeness, minimizing risks in training datasets.
• Collaborate with model training teams to identify and resolve bottlenecks in dataset performance.
• Provide leadership on data quality strategy and establish internal best practices.
• Evaluate external datasets for integration, focusing on scalability and relevance, and create data scorecards.
• Contribute to the development of tools for automated data preprocessing and validation.
• Competitive compensation package with performance-based incentives.
• Fully remote and flexible working arrangements.
• Opportunity to work on impactful AI projects with advanced datasets.
• Collaborative culture emphasizing velocity, impact, and experimentation.
• Direct influence on AI model performance and data quality strategy.