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Tier-1 brand, metro location, and a popular mid-level data scientist title increase candidate competition.
Core ML and production data science skills transfer across industries, but CPG-specific domain knowledge moderately matters.
Explicit 5+ years requirement and mandatory Python, SQL, cloud, and ML expertise make filters stringent.
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Lead end-to-end data science projects including data collection, model development, deployment, and performance monitoring across multiple ABI markets.
Build scalable, reusable Python-based ML pipelines and improve code standardization to support AI-driven solutions at scale.
Collaborate with senior management and business stakeholders to create analytics roadmaps and translate complex data insights into actionable business strategies.
5+ years hands-on experience in data science or analytics with proven ability to build, deploy, and maintain ML models in production.
Bachelor's or master's degree in Computer Science, Information Systems, AI, Data Science, Machine Learning, Economics, or related field (B.Tech/BE/Masters).
Proficiency in advanced Python programming for ML pipelines, intermediate to advanced SQL, and Excel skills; experience with Git and any cloud platform (Azure, AWS, GCP, or Databricks).
Expertise in multiple statistics and ML techniques (classification, regression, forecasting, recommendation, optimization) and Object-Oriented Programming in Python.
Experienced in managing and mentoring data science teams with a focus on scalable AI product integration and operationalizing ML workflows.
Comfortable working closely with cross-functional teams including product and engineering, using Agile delivery practices.
Strong strategic orientation towards building large-scale, robust AI-powered products with emphasis on code quality, standardization, and emerging AI trends.