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Tier-1 brand, metro locations, mid-level generalist ML/GenAI role with broad skillset drives high competition.
Requires transferable ML/GenAI skills but prefers industry domain experience, so medium background sensitivity.
Explicit 1–5 years plus mandatory GenAI, Python, cloud and MLOps skills indicates high shortlisting strictness.
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Develop and deploy advanced machine learning models and Generative AI applications using Python, SQL, and cloud platforms (Azure, AWS, GCP).
Manage end-to-end MLOps pipelines including model training, monitoring, and scalability for business-critical projects.
Create dashboards and data-driven reports (PowerBI/Tableau) to present model impact and recommendations to stakeholders.
1-5 years of professional experience in data science.
Bachelor's or master's degree in computer science, statistics, applied mathematics, or related field.
Proficiency in Python, SQL, PySpark, and experience with cloud platforms such as Azure, AWS, or GCP.
Hands-on experience with Generative AI application development and production deployment.
Experience delivering data science projects in Utilities, Oil & Gas, Mining, Manufacturing, Chemicals, or Forest Products industries.
Demonstrated capability in integrating Generative AI solutions with existing enterprise systems including API development.
Skilled in MLOps pipeline implementation and cloud-native tools (e.g., Databricks, AzureML, AWS Lambda) for scalable deployments.