        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: 6/10  
        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 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, it lacks evidence of hands-on experience in designing, developing, and maintaining data pipelines, data cleaning, transformation, or creating data visualizations and dashboards. The candidate's focus appears to be more on machine learning and AI projects rather than data engineering tasks.</li>
    <li>The candidate has less than one year of relevant experience, which partially meets the requirement of 0 to 1 year. However, the experience is primarily in machine learning and AI development rather than data engineering, which reduces the relevance.</li>
    <li>The educational qualification aligns well with the job requirements. The candidate is pursuing a Bachelor of Technology in Computer Science with a specialization in AI & ML, which is closely related to the required disciplines.</li>
    <li>The candidate possesses some of the required skills, such as Python (with libraries like Pandas, Matplotlib, and Seaborn) and MySQL. However, there is no explicit mention of Power BI or Excel skills, which are critical for the role. The resume also lacks evidence of proficiency in writing reusable and modular code or familiarity with Jupyter Notebook.</li>
    <li>The candidate's domain knowledge is more focused on machine learning and AI rather than data engineering or information technology. While there is some overlap, the lack of specific data engineering experience reduces the fitment score for this criterion.</li>
    <li>The candidate demonstrates strong problem-solving skills and communication abilities through project work and internships. However, there is limited evidence of collaboration with cross-functional teams, attention to detail in data engineering tasks, or documentation of workflows and processes.</li>
    <li>The certifications listed are relevant to machine learning and deep learning but do not directly align with the required certifications for Python, MySQL, Power BI, or Excel. This reduces the score for this criterion.</li>
</ol>
```