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Mid-level ML role in a metro with strong employer brand and broad skill requirements driving high competition.
Core ML, Python, and SQL skills are transferable, but some banking domain preference implies medium sensitivity.
Explicit 6-7 years plus must-have ML, Python, SQL, and NLP create high shortlisting strictness.
Own the development and deployment of AI/ML models aligning with enterprise strategy, covering full project lifecycle from data prep to production.
Design, build, and optimize classical AI/ML algorithms and validate them using statistical and machine learning evaluation techniques.
Communicate technical findings and methodologies clearly to non-technical stakeholders and ensure data quality and reliability throughout the process.
6-7 years of hands-on experience in Data Science.
Strong proficiency in statistical data analysis, machine learning, and natural language processing.
Advanced skills in Python programming and SQL with relevant libraries.
Competency in software development methodologies and version control tools.
Experienced in end-to-end AI/ML projects including model design, infrastructure setup, and lifecycle management with familiarity in MLOps.
Comfortable working in multidisciplinary teams and translating technical outputs for non-technical stakeholders.
Has solid foundations in classical ML algorithms, feature engineering, and statistical analysis to deliver scalable ML solutions.