1. Roles & Responsibilities: 2/10
2. Years of Experience: 2/10
3. Education Qualification: 10/10
4. Skills/Knowledge: 2/10
5. Domain/Industry: 4/10
6. Key Competencies: 4/10
7. Certifications: 2/10

<h5 style="font-family: Roboto; font-size: 0.88rem; font-weight: bold;">Overall Summary-</h5>
<ol style="font-family: Roboto; font-size: 0.88rem; max-width: 100vw;">
  <li>
    The candidate’s resume demonstrates strong academic credentials with a Bachelor of Technology, fully meeting the educational requirement.
  </li>
  <li>
    There is insufficient evidence of 1-2 years of relevant professional experience in data annotation, labeling, or related tasks. The internship and project work do not clearly indicate duration or relevance to annotation roles.
  </li>
  <li>
    The resume lacks direct mention or contextual evidence of hands-on experience with data annotation tools (e.g., Labelbox, Supervisely, CVAT, VGG Image Annotator), image/video labeling, audio transcription, translation, or 2D/3D annotation. The focus is on machine learning, NLP, and AI application development.
  </li>
  <li>
    While the candidate has experience in Python, Pandas, and data preprocessing, there is no indication of proficiency in annotation-specific data formats (CSV, JSON, XML) as related to annotation workflows, nor experience with quality assurance or validation of annotated data.
  </li>
  <li>
    The domain experience is primarily in IT and data science, which is tangentially relevant, but there is no direct exposure to annotation project workflows or the specific domain requirements outlined.
  </li>
  <li>
    Key competencies such as attention to detail, consistency, and annotation precision are not substantiated. The resume highlights technical and analytical skills but does not demonstrate annotation-specific competencies or teamwork in annotation contexts.
  </li>
  <li>
    Certifications listed are generic (Data Science, Python, SQL, Streamlit) and do not align with annotation tools, data labeling, or related sub-skills required for the role.
  </li>
  <li>
    Overall, the resume does not provide evidence of fit for a data annotation or labeling role as described in the job requirements. The candidate’s strengths are in AI, machine learning, and software development, not in annotation, labeling, or transcription.
  </li>
</ol>