Data Coordinator - (Annotation, Review & MEL)
- Annotate user queries sequentially within each session while considering previous queries and responses to maintain conversational continuity and context.
<\/span><\/li>- Translate corrected user queries into clear and grammatically accurate English while preserving the original meaning and intent.
<\/span><\/li>- Rephrase user queries into complete standalone English queries using the current query, chat history, and available metadata for effective answer generation.
<\/span><\/li>- Identify and map crops mentioned in queries to the standardized crop list and assign the appropriate advisory category based on query intent and context.
<\/span><\/li>- Ensure consistency, accuracy, completeness, and adherence to project annotation guidelines, SOPs, confidentiality, and quality standards.
<\/span><\/li>- Review annotated sessions to validate translations, rephrased queries, crop mapping, advisory category mapping, and contextual understanding incorporated during annotation.
<\/span><\/li>- Identify inconsistencies, ambiguities, missing information, annotation errors, and potential biases, and provide corrective feedback to improve annotation quality and dataset reliability.
<\/span><\/li>- Ensure standardized interpretation and uniformity across the dataset, with each session handled by a single annotator and independently reviewed for quality assurance.
<\/span><\/li>- Validate agricultural advisories, pest management protocols, and crop\-related recommendations against established agronomic literature and extension advisories.
<\/span><\/li>- Create and maintain high\-quality ground\-truth datasets, document evaluation decisions, and follow standardized evaluation protocols.
<\/span><\/li>- Evaluate AI\-generated responses for accuracy, relevance, completeness, and alignment with recommended agricultural practices.
<\/span><\/li>- Identify incorrect, incomplete, or misleading AI responses, flag knowledge gaps, and provide structured feedback to support model refinement and improvement.
<\/span><\/li>- Participate in calibration and review discussions to maintain evaluation consistency and support continuous enhancement of the AI system.
<\/span><\/li>- Perform additional tasks related to annotation, review, evaluation, and quality assurance as assigned by the supervisor or project team.<\/span>
<\/li><\/ul>
<\/div><\/span>Requirements<\/h3>
- Education: Master\u2019s degree (Second or Third or Fourth year) or PhD (Any year) in Entomology, Plant Pathology or Agronomy from an accredited university or college. Students pursuing a degree can also participate in.<\/span><\/span><\/span><\/span><\/span>
<\/span><\/span><\/li>- Experience: Experience working with or training farmers is required.<\/span><\/span><\/span><\/span><\/span>
<\/span><\/span><\/li>- Domain Knowledge: Strong understanding of crops, common plant diseases, pest identification, and agronomic terminology. Ability to assess the correctness of crop\-related annotations is essential.<\/span><\/span><\/span><\/span><\/span>
<\/span><\/span><\/li>- Tools Availability: Access to a functional laptop and a reliable internet connection is mandatory.<\/span><\/span><\/span><\/span><\/span>
<\/span><\/span><\/li>- Technical Skills: Proficient with multitasking in a split\-screen setup, using Excel or Google Sheets, and performing data entry and copy\-paste operations efficiently.<\/span><\/span><\/span><\/span><\/span>
<\/span><\/span><\/li>- Communication Skills: Strong verbal and written communication skills to participate in team calls, deliver feedback effectively, and coordinate with the project team.<\/span><\/span><\/span><\/span><\/span>
<\/span><\/span><\/li>- Collaboration: Ability to work effectively with geographically dispersed teams and in multicultural environments.<\/span><\/span><\/span><\/span><\/span>
<\/span><\/li><\/ul>
<\/div><\/span> - Experience: Experience working with or training farmers is required.<\/span><\/span><\/span><\/span><\/span>
- Translate corrected user queries into clear and grammatically accurate English while preserving the original meaning and intent.