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Strong employer brand, mid-level generalist ML role, and metro location increase applicant competition.
Core ML and decision-science skills are broadly transferable across industries.
Explicit six-year requirement and preferred advanced degree make candidate filters strict.
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Lead analysis of complex datasets to extract actionable insights and trends.
Develop and deploy predictive models and optimization techniques to improve business outcomes and resource allocation.
Design and implement decision support systems and lead cross-functional teams to align analytics with business priorities and assess impact on key metrics.
Bachelor's degree or equivalent in Computer Science, MIS, Mathematics, Statistics, or related field; Master's or PhD preferred.
At least 6 years of relevant work experience in decision science for the Lead II level.
Proficiency in data analysis, predictive modeling, optimization, experimental design, and programming skills.
Fluency in English required.
Experienced in leading cross-functional teams and managing end-to-end analytical projects in decision science.
Strong technical expertise in statistical modeling, machine learning, and decision support system design.
Ability to translate complex data insights into actionable business strategies and to iterate on models based on impact evaluation.