        1. Roles & Responsibilities: 2/10  
        2. Years of Experience: 4/10  
        3. Education Qualification: 8/10  
        4. Skills/Knowledge: 6/10  
        5. Domain/Industry: 4/10  
        6. Key Competencies: 4/10  
        7. Certifications: 6/10  

```html
<h5 style="font-family:Roboto; font-size:0.88rem; font-weight:bold;">Overall Summary</h5>
<ol style="font-family:Roboto; font-size:0.88rem; line-height:1.5;">
    <li>The candidate's experience does not align well with the specific roles and responsibilities outlined in the job requirements. While the resume demonstrates experience in machine learning and AI projects, there is limited evidence of work related to data pipelines, data cleaning, transformation, validation, or creating dashboards and visualizations. This results in a low score for roles and responsibilities.</li>
    <li>The candidate has less than one year of relevant experience, which aligns partially with the job requirement of 0-1 year. However, the internships listed are not directly related to data engineering, leading to a moderate score in this category.</li>
    <li>The candidate holds a Bachelor of Technology in Computer Science with a specialization in AI & ML, which is closely related to the required educational qualification. This results in a high score for education qualification.</li>
    <li>The resume lists several technical skills, including Python, Pandas, Matplotlib, Seaborn, MySQL, and Excel, which align with the primary skills required for the role. However, there is no explicit mention of Power BI or Jupyter Notebook, and the context of using these skills in data engineering tasks is limited. This leads to an average score for skills/knowledge.</li>
    <li>The candidate's domain knowledge appears to be more focused on machine learning and AI rather than data engineering or IT. While there is some overlap, the lack of direct experience in the data engineering domain results in a moderate score for domain/industry knowledge.</li>
    <li>The resume highlights soft skills such as teamwork, communication, and problem-solving. However, there is insufficient evidence of competencies like attention to detail, collaboration with cross-functional teams, or documentation of workflows, which are critical for the role. This results in a moderate score for key competencies.</li>
    <li>The candidate has completed certifications in machine learning, deep learning, and networking, which demonstrate a proactive learning attitude. However, there are no certifications directly related to Power BI, MySQL Workbench, or Excel, which are critical for the role. This leads to an average score for certifications.</li>
</ol>
```