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High due to Tier-1 brand, metro location, popular ML role, and broad technical requirements.
Medium because ML and deployment skills are transferable, though domain knowledge increases specificity.
High due to extensive mandatory ML, deployment, cloud, and full-stack technical requirements.
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Identify data-driven opportunities and develop business solutions through collaboration with stakeholders.
Design, develop, and deploy scalable AI/ML/statistical models and algorithms customized for multiple business units.
Lead projects independently, provide technical mentorship, and create interactive dashboards to communicate insights.
Bachelor’s degree in Engineering (B.E).
Proficiency in Python for data preprocessing, feature engineering, and QA.
Experience with advanced machine learning algorithms including regression, classification, clustering, SVM, decision trees, random forests, and neural networks.
Work Experience Required: Not explicitly mentioned in the JD.
Strong ability to lead product and project initiatives independently and mentor technical teams.
Experience collaborating across functions including product, engineering, and business units to deliver solutions.
Skilled in deploying models to cloud platforms (Azure/AWS) with containerization (Docker) and CI/CD pipelines.