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Metro location, popular Data Scientist role, and broad multi-skill requirements increase candidate competition.
ML/AI skills transfer across industries, but forecasting and ERP domain needs increase sensitivity.
Multiple mandatory ML, MLops, cloud, and deployment skills increase screening rigor.
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Lead end-to-end AI/ML solution development including algorithm selection, model optimization, deployment, and lifecycle management to ensure scalable production-grade systems delivering measurable business impact.
Collaborate across business SMEs, functional leads, and IT to deploy scalable AI/ML-infused systems aligned with strategic growth initiatives.
Analyze and mine enterprise data using advanced analytics, statistics, and machine learning to derive actionable insights and guide business recommendations.
Bachelor’s degree in Mathematics, Statistics, Computer Science, Data Analytics/Science, or related field.
Proficiency in Python coding and experience with architecting scalable data solutions, preferably in Azure cloud environment.
Demonstrated expertise in full ML workflow: training, applying, integrating, optimizing, deploying, and scaling AI/ML models including timeseries and NLP applications.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in implementing production-grade AI/ML solutions with strong focus on model lifecycle management and ML Ops.
Ability to communicate complex analytics results effectively to business leaders and translate strategy into actionable analytic insights.
Experienced working with cross-functional and cross-cultural teams globally, with fluency in English and demonstrated leadership/consultation abilities.