Back
Strong Tier-1 brand, visible data science role, and metro mid-seniority increase candidate competition.
Advanced ML skills transfer broadly, but healthcare, logistics, and manufacturing domain expertise raise sensitivity.
Mandatory 7+ years, Master's/PhD, and specific MLOps/tech stack make hiring filters highly strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Architect and implement scalable AI/ML solutions supporting strategic priorities like commercial excellence, logistics, inventory, and manufacturing.
Lead technical efforts integrating data science with data engineering, ML engineering, GenAI, and finance to deliver end-to-end solutions.
Ensure data science projects drive measurable business outcomes such as revenue growth, operational efficiency, and inventory optimization.
7+ years of direct AI/ML experience building and deploying enterprise-grade solutions.
Masters or PhD in Computer Science, AI, Data Science, Applied Mathematics, or related field.
Proficiency in ML algorithms, GenAI frameworks, Python, AWS/Azure, and tools like R, SQL, Spark, TensorFlow, Keras, PyTorch, Scikit-learn.
Experience with MLOps including deployment, monitoring, and maintenance of ML/GenAI models in production environments.
Demonstrated ability to solve real-world business problems in forecasting, pricing, customer analytics, sales planning, computer vision, and operational optimization.
Experience working cross-functionally in hybrid/virtual teams and communicating complex technical concepts to senior non-technical stakeholders.
Comfortable leading technical teams and promoting best practices for scalable and reliable AI/ML solutions.