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Mid-level ML role with popular skills, metro hiring, and broad requirements creates high competition.
Core ML, MLOps, and data engineering skills are highly transferable across industries.
Explicit 3–6 year requirement plus mandatory Python, PySpark, SQL and ML/MLOps skills enforce medium strictness.
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Implement, test, validate, monitor, and report on analytical solutions to ensure accuracy and operational stability.
Extract, analyze, and validate large datasets using Python, PySpark, SQL, and Hadoop to support analytics implementations and model scoring.
Support automation, AI-driven tools, and MLOps/LLMOps processes for deployment, monitoring, and governance of AI/ML solutions.
3 to 6 years of relevant experience in Data Analytics / Data Science roles.
Strong programming skills in Python, PySpark, and SQL.
Knowledge of LLM tools, GenAI concepts, and modern AI techniques.
Work Experience Required: 3 to 6 years in Data Analytics/Data Science.
Experienced in developing and supporting AI/ML solutions with operational efficiency and automation.
Familiar with AI/ML model monitoring, observability, and workflow orchestration frameworks.
Ability to translate complex data into meaningful business insights and maintain technical documentation.