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Tier-1 employer, metro role, popular ML title and broad ML/NLP skillset create moderate competition.
Role requires deep ML/NLP and deployment/MLOps expertise, limiting transfers from non-ML backgrounds.
Explicit 6-7 years plus multiple must-have ML, NLP, Python, SQL and MLOps requirements increases strictness.
Own end-to-end development and deployment of AI/ML models including data preparation, exploratory analysis, modeling, validation, and production support.
Develop high-impact AI/ML use cases aligned with organizational objectives using classical AI/ML algorithms and statistical techniques.
Communicate analytical insights and methodologies effectively to non-technical stakeholders and collaborate with multidisciplinary teams to deliver measurable results.
6-7 years of hands-on experience in Data Science.
Expertise in statistical data analysis, machine learning, and natural language processing with practical understanding of constraints.
Advanced proficiency in Python programming and SQL with relevant libraries for data analysis.
Competency in software development methodologies, version control tools, and basic familiarity with MLOps.
Experienced data scientist comfortable handling full ML lifecycle from data prep to deployment in enterprise settings.
Strong domain and technical expertise in classical ML algorithms, feature engineering, and model evaluation methodologies.
Can translate complex AI/ML concepts to non-technical stakeholders and aligns solutions with business strategy.