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

Descriptive Analysis:
Overall Summary:
The candidate's resume shows a good fitment to the job requirements, with strengths in roles & responsibilities, skills/knowledge, and key competencies. However, there are some weaknesses in the years of experience and domain/industry knowledge.

- Roles & Responsibilities: The candidate's resume demonstrates experience in analyzing large datasets, developing and implementing machine learning algorithms, and creating data visualizations. They also mention collaborating with cross-functional teams and staying updated with the latest advancements in machine learning and AI. These experiences align well with the job requirements, earning a score of 6/10.

- Years of Experience: The candidate's resume does not explicitly mention their years of experience in the field of data science. However, they mention working as a data science intern and having comprehensive understanding and skills in data science. Based on this information, the candidate's experience is somewhat relevant, earning a score of 4/10.

- Education Qualification: The candidate holds an MBA in Human Resource and a Bachelor's degree in Electronics & Telecommunication. While their educational qualifications do not directly align with a Master of Computer Science, they do have relevant certifications in data science and AI. Considering this, their education qualification is somewhat relevant, earning a score of 4/10.

- Skills/Knowledge: The candidate's resume showcases proficiency in Python, machine learning, artificial intelligence, deep learning, and data cleaning. They also mention experience with statistical analysis, data visualization, and various machine learning algorithms. Additionally, they have familiarity with Python, Java, MongoDB, NLP, PyTorch, and CI/CD. These skills align well with the job requirements, earning a score of 8/10.

- Domain/Industry: The candidate's resume does not explicitly mention knowledge of the artificial intelligence industry. This is a weakness as it is a nice-to-have requirement. Therefore, the candidate's fitment in this area is less relevant, earning a score of 2/10.

- Key Competencies: The candidate's resume highlights analytical thinking, problem-solving, strong programming skills, data-driven decision-making, communication skills, and mentoring and leadership abilities. These competencies align well with the job requirements, earning a score of 8/10.

Overall, the candidate's resume demonstrates a good fitment to the job requirements, with strengths in roles & responsibilities, skills/knowledge, and key competencies. However, there are weaknesses in the years of experience and domain/industry knowledge.