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Tier-1 brand, metro location, generalist Data Scientist title, and mid-level profile raise competition.
ML/AI skills are broadly transferable, though retail domain knowledge provides some bias.
Moderate due to specific ML, deep learning, and engineering stack requirements without explicit years.
Develop, implement, and maintain predictive algorithms using machine learning, deep learning, GenAI, NLP, or computer vision to optimize business decisions.
Produce well-structured, tested, and documented code in Python, SQL, Hadoop/Hive, or other approved languages following agile processes and best programming practices including unit tests and CI/CD basics.
Collaborate within Data Sciences team and across geographies to translate business problems into data science solutions, present findings, and participate in code reviews.
Bachelor's degree in quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience.
Strong foundations in mathematics including probability, statistics, and linear algebra.
Hands-on programming skills in Python, SQL, Hadoop/Hive, and experience with ML engineering.
Work Experience Required: Not explicitly mentioned in the JD.
Comfortable applying advanced machine learning, deep learning, computer vision, and GenAI techniques to solve real-world business problems.
Ability to communicate data-driven insights effectively through visualizations and narratives to technical and non-technical stakeholders.
Experience working in agile, collaborative environments distributed across multiple time zones and geographies.