1. Roles & Responsibilities: 8/10
2. Years of Experience: 10/10
3. Education Qualification: 10/10
4. Skills/Knowledge: 8/10
5. Domain/Industry: 10/10
6. Key Competencies: 8/10
7. Certifications: 9/10

<h5 style="font-family:Roboto;font-size:0.88rem;"><b>Overall Summary</b></h5>
<ol style="font-family:Roboto;font-size:0.88rem;">
  <li><b>Roles & Responsibilities:</b> The candidate has led multiple AI/ML projects involving Generative AI, NLP, and deep learning. Responsibilities include solution architecture, team leadership, and client management. There is strong evidence of model development, testing, and deployment. However, explicit mention of clustering tasks, SQL querying, and MLOps practices is limited, which slightly reduces the score.</li>
  <li><b>Years of Experience:</b> The resume clearly states over 14 years of R&D experience and 8 years in AI/ML/Data Science, aligning perfectly with the requirement of 12–15 years. Full marks awarded.</li>
  <li><b>Education Qualification:</b> The candidate holds a PhD in Machine Learning and M.Tech/B.E. in Electronics and Communication Engineering from reputed institutions. This exceeds the basic educational expectations. Full marks awarded.</li>
  <li><b>Skills/Knowledge:</b> Strong proficiency in Python, Pandas, NumPy, Scikit-learn, TensorFlow, Keras, and Matplotlib is demonstrated. Experience with LLMs, OpenAI, GPT-4, and NLP is evident. However, there is no mention of SQL, MySQL, PostgreSQL, Spark, Hadoop, Databricks, Azure Data Factory, or Cosmos Scope scripts. Azure deployment is not explicitly stated, which is a significant gap under strict evaluation.</li>
  <li><b>Domain/Industry:</b> The candidate has deep involvement in AI/ML, NLP, and Generative AI across academia and industry. Projects span insurance, healthcare, and speech recognition, showing strong domain alignment. Full marks awarded.</li>
  <li><b>Key Competencies:</b> Demonstrated leadership, problem-solving, and cross-functional collaboration. Strong communication skills are evident through multilingual fluency and extensive publication record. However, model performance metrics (precision, recall, AUC) and stakeholder communication via dashboards or reports are not explicitly detailed.</li>
  <li><b>Certifications:</b> The candidate holds multiple relevant certifications from IBM, Stanford, DeepLearning.AI, Microsoft, and Google Cloud in Python, ML, Deep Learning, and Data Science. However, certifications in SQL, MLOps, or Azure-specific tools are not listed, slightly reducing the score.</li>
</ol>