Data Labeler (Dutch intermediate speaker)

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Data Labeler (Dutch intermediate speaker) based in Brazil. This is a remote opportunity to contribute to international projects involving historical records, multilingual data, and large-scale data quality initiatives. You’ll collect, clean, review, and validate historical family records using specialised data extraction tools. The role combines data labelling, research, pattern recognition, and language skills to transform complex historical information into accurate, structured datasets. You’ll collaborate with colleagues and cross-functional teams in an international and multicultural environment. Your ability to interpret Dutch at an intermediate level will be particularly important when working with historical documents and records. The position is well suited to someone who is analytical, curious, highly detail-oriented, and comfortable investigating unfamiliar information. You’ll also have opportunities to develop your research, data, language, and technical skills while contributing to international projects.

Collect, clean, process, and organise historical family records from a variety of sources using internal data extraction tools. Review historical documents and datasets to identify relevant information, inconsistencies, relationships, and patterns. Read and interpret Dutch-language historical records at an intermediate level or above. Identify patterns, relationships, anomalies, names, dates, locations, and other relevant details within complex historical data. Conduct research to investigate unfamiliar people, places, dates, family relationships, and historical records. Validate data findings and collaborate with colleagues to ensure information is accurate and reliable. Document research findings and data decisions clearly and consistently. Review and validate historical data for accuracy, completeness, consistency, and quality. Work with cross-functional teams to integrate research findings and contribute to broader data-quality initiatives. Share findings and collaborate with peers to improve understanding and interpretation of historical family records. Requirements: Intermediate or higher ability to read and interpret Dutch , which is an essential requirement for the role. Intermediate to advanced English proficiency for communication and collaboration within an international, multicultural team. Bachelor’s degree in Data Science, Humanities, History, Linguistics, or a related field , or equivalent academic/professional experience. Entry- to mid-level professional experience in data science, data labelling, data annotation, research, historical research, or a related field. Strong analytical and problem-solving skills, with the ability to evaluate information critically and identify meaningful patterns. Excellent attention to detail and perseverance when working with historical records, inconsistent datasets, and difficult-to-read documents. Strong pattern-recognition skills and the ability to identify relationships, discrepancies, and anomalies. Good written and verbal communication skills, with the ability to explain findings and research conclusions clearly. A curious and investigative mindset, particularly when researching unfamiliar names, places, dates, languages, and historical documents. Willingness to learn how to interpret additional languages and historical materials. Ability to work independently while collaborating effectively with colleagues in a remote, multicultural environment. Strong commitment to accuracy, consistency, and data quality. Availability to work a schedule aligned with Salt Lake City, Utah (Mountain Time), or a nearby time zone . Benefits: Fully remote work arrangement within Latin America , with the opportunity to work from Brazil. Competitive salary. Flexible working hours aligned with the project's operating schedule. Professional development and training opportunities. Opportunity to develop skills in data labelling, research, multilingual data, and historical record analysis. Exposure to international projects involving historical records and complex multilingual datasets. Collaborative and inclusive environment with colleagues from diverse cultural and professional backgrounds. Opportunity to contribute to projects with an international scope while working remotely. Experience working with specialised data extraction and validation tools.

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