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Tier-1 brand, mid-level ML role, metro location, and broad skillset requirements increase applicant competition.
Core ML and optimization skills are transferable across industries, though logistics domain knowledge is beneficial.
Explicit Senior II years requirement plus mandatory decision-science and modeling skills create strict shortlisting filters.
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Analyze complex data sets to extract actionable insights and trends that inform business decisions.
Develop, deploy, and iterate predictive and optimization models to improve business outcomes and resource allocation.
Design decision support systems and experiments to evaluate and enhance business strategies in collaboration with cross-functional teams.
Bachelor's degree or equivalent in Computer Science, MIS, Mathematics, Statistics, or similar discipline; Master's or PhD preferred.
Minimum 5 years relevant experience in decision science (Senior II level).
Proficiency in data modeling, programming, statistical and mathematical knowledge.
Fluency in English.
Experienced in advanced predictive modeling, optimization, and experimental design within a business context.
Able to collaborate effectively with diverse stakeholders to translate business requirements into data-driven solutions.
Continuously updates knowledge on machine learning, decision science, and analytics to enhance impact.