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Tier-1 brand, metro location, and broad analytics/GenAI skill requirements increase candidate competition.
Applied AI and customer-analytics emphasis requires domain familiarity, though core ML skills are transferable.
Explicit 7+ years and mandatory applied AI, GenAI, and large-scale analytics skills enforce strict filtering.
Translate complex business questions into data analysis, define data needs, and develop roadmaps for open-ended problems.
Lead AI and advanced analytics solution development, validate methodologies, and drive scalable business decisions.
Build AI agents and decision intelligence solutions using LLMs and enterprise data to impact customer behavior and business growth.
Bachelor's or postgraduate degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or related field.
Minimum 7 years of experience in Applied AI, Data Science, Decision Science, Product/Business/Customer Analytics, Forecasting, or intelligent analytics platform development.
Strong programming skills in Python and SQL with experience in large scale data analysis and working with structured and unstructured data including text sources.
Experience using GenAI tools (e.g., Claude, Copilot) and proven expertise in experimentation, A/B testing, customer segmentation, forecasting, and behavioral analytics.
Experienced in translating complex customer lifecycle metrics and behavioral insights into scalable business decisions and actionable solutions.
Proven ability to lead and mentor teams in advanced analytics and AI solution architecture within collaborative, cross-functional environments.
Demonstrates thought leadership in Decision Science and AI, with a strong data-driven storytelling approach to influence business outcomes.