        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;">
    <li>The candidate's resume demonstrates limited alignment with the roles and responsibilities outlined in the job requirements. While there is evidence of technical projects and internships, they are primarily focused on machine learning and AI rather than data engineering tasks such as data pipeline design, data cleaning, or dashboard creation. This results in a low score for this section.</li>
    <li>The candidate has 0-1 year of experience, which aligns with the job requirement. However, the experience is not directly related to data engineering but rather machine learning and AI development, leading to a moderate score.</li>
    <li>The candidate holds a Bachelor of Technology in Computer Science with a specialization in AI & ML, which is relevant to the educational qualification requirement. This earns a high score in this section.</li>
    <li>The resume lists skills such as Python, Pandas, Matplotlib, Seaborn, MySQL, and SQLAlchemy, which partially align with the required skills. However, there is no explicit mention of Power BI or Excel, and the focus is more on machine learning frameworks rather than data engineering tools. This results in an average score for skills/knowledge.</li>
    <li>The candidate's domain experience is primarily in machine learning and AI, with no explicit mention of data engineering or IT department experience. This leads to a below-average score for domain/industry knowledge.</li>
    <li>The resume mentions soft skills like teamwork, communication, and problem-solving, but there is limited evidence of competencies such as attention to detail, documentation, or collaboration with cross-functional teams in the context of data engineering. This results in a low score for key competencies.</li>
    <li>The candidate has certifications in machine learning and deep learning, which are somewhat relevant but not directly aligned with the required certifications in Python, MySQL, Power BI, or Excel. This earns a moderate score in the certifications section.</li>
</ol>
```