Data Labeler (Dutch intermediate speaker)
在海因斯恩，我们与北美和拉塔姆的客户合作，在灵活，多元化和多元文化环境中建立创新解决方案。我们热衷于技术，持续学习和协作 - 我们希望你成为这一增长的一部分。我们正在寻找一个数据标签师加入我们的团队并为高影响的国际项目取得成功贡献专业知识。关键责任 · 数据收集和清洁：从各种来源收集，清洁和处理历史家族记录，通过我们的内部数据提取工具确保数据质量和准确性。· 模式识别：识别多种语言的家庭记录和历史文件中的模式，关系和异常。· 历史研究：与同行合作验证数据发现并有助于更好地理解家族史。· 协作：与跨功能团队合作整合和验证数据结果。· 文档和数据验证：审查，记录和验证历史数据以确保一致性，准确性和完整性。资格 · 具体语言要求：在中级或以上水平上阅读和解释荷兰语是必不可少的。· 英语：需要中级到高级英语水平，因为这项角色涉及与国际多元文化团队合作。· 教育：数据科学，人文学，历史，语言学或相关领域的本科士学位。也可以考虑相当的学术或专业经验。· 经验：进入中层面的专业人员在数据科学，数据标签，数据注释，研究或相关领域有经验。•分析技能：强大的解决问题能力和批判性和分析思考的能力。· 沟通：良好的口头和书面交流技巧，具有清晰解释发现和概念的能力。· 注意细节：· 历史记录和难以阅读的文件工作时，坚持谨慎地处理细节。· 模式识别：能够识别历史文档和数据集中的图案，关系和不一致性。·语言技能：学习阅读和解释其他语言和历史文档的兴趣。· 研究思维方式：好奇心和调查未知名字，地点，日期和历史记录的意愿。
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At Heinsohn, we partner with clients across North America and LATAM, building innovative solutions in an agile, diverse, and multicultural environment. We are passionate about technology, continuous learning, and collaboration - and we want you to be part of this growth.
We are looking for a Data Labelerto join our team and bring expertise that will contribute to the success of high-impact international projects.
Key Responsibilities
- Data Collection and Cleaning: Collect, clean, and process historical family records from various sources, ensuring data quality and accuracy using our in-house data extraction tool.
- Pattern Recognition: Identify patterns, relationships, and anomalies in family records and historical documents across multiple languages.
- Historical Research: Collaborate with peers to validate data findings and contribute to a better understanding of family histories.
- Collaboration: Work with cross-functional teams to integrate and validate data findings.
- Documentation and Data Validation: Review, document, and validate historical data to ensure consistency, accuracy, and completeness.
Qualifications
- Specific Language Requirement: Ability to read and interpret Dutch at an intermediate level or higher is essential for this role.
- English: Intermediate to advanced English proficiency is required, as the role involves working with an international, multicultural team.
- Education: Bachelor’s degree in Data Science, Humanities, History, Linguistics, or a related field. Equivalent academic or professional experience may also be considered.
- Experience: Entry- to mid-level professional with some experience in data science, data labeling, data annotation, research, or a related field.
- Analytical Skills: Strong problem-solving skills and the ability to think critically and analytically.
- Communication: Good verbal and written communication skills, with the ability to explain findings and concepts clearly.
- Attention to Detail: Strong perseverance and attention to detail when working with historical records and difficult-to-read documents.
- Pattern Recognition: Ability to identify patterns, relationships, and inconsistencies in historical documents and datasets.
- Language Skills: Interest in learning to read and interpret additional languages and historical documents.
- Research Mindset: Curiosity and willingness to investigate unfamiliar names, places, dates, and historical records.
Additional Information
- Location: Remote – Latin America (LATAM).
- Work Schedule: The work schedule aligns with Salt Lake City, Utah (Mountain Time) or nearby time zones.
- The position involves working with an international and multicultural team.
Benefits
- Competitive salary.
- Flexible work hours and remote work.
- Professional development and training opportunities.
- Inclusive and collaborative work environment with a multicultural team.
- Opportunity to work on international projects involving historical records and multilingual data.
Ready to take your talent to the next level?
At Heinsohn, we value innovation, passion for technology, and teamwork. If this sounds like your next challenge, apply today and let’s make history together! ✨
Originally posted on Himalayas