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Tier-1 brand, metro location, and broad technical scope increase candidate density and competition.
Core ML and big-data skills transfer well, though senior stakeholder context increases domain specificity.
Mandatory 10+ years, deep ML/big-data expertise, and vendor-management requirements make filters stringent.
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Partner with business and IT to ensure appropriate access to data and provide advanced enterprise-wide data analysis and insights.
Design and guide development of strategic cross-functional data solutions, data models, and data visualizations to support organizational goals and roadmaps.
Lead vendor management, project management, and quality assurance processes for data products and solutions.
Minimum 10+ years of relevant experience in data science or related fields.
Bachelor's degree in Data Science, Computer Science, or Machine Learning.
Expertise in data modeling, predictive analytics (regression, clustering, decision trees, neural networks), and Big Data technologies (MapReduce, Hive, Spark, Kafka, Yarn, Storm).
Experience in software engineering with scripting, data visualization (Java/J2EE, JavaScript, React.js, D3, etc.) and proven vendor management capabilities.
Experienced in strategic design and implementation of global, cross-functional data science solutions aligned with business objectives.
Able to translate high-level executive requirements into actionable plans and influence stakeholders through trusted communication.
Demonstrates deep technical expertise coupled with strong business acumen in enterprise data architecture, analysis, and emerging technologies.