AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

• The candidate possesses strong skills and experience in Data Science, Machine Learning, and predictive analytics, including Python, SQL, various ML algorithms (XGBoost, Random Forest, K-Means, NLP), and data preprocessing techniques.
• Demonstrated ability to lead projects, optimize models, and translate data insights into business value (e.g., 94% accuracy in credit default prediction, 25% churn reduction, 12% revenue increase).
• The candidate's entire professional background and skill set are exclusively focused on Data Science, which presents a significant mismatch for a QA Automation Engineer role. There is no evidence of experience or skills in software testing, test automation frameworks, CI/CD for testing, or quality assurance methodologies.