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Senior 10+ years and niche MLOps/governance focus reduce applicant density despite remote posting.
Role requires deep ML/AI platform, MLOps, and governance expertise, limiting cross-industry transferability.
Explicit 10+ years, mandatory AWS MLOps experience, and regulated governance requirements increase filter strictness.
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Lead evaluation-driven development strategy and standards for AI/ML and analytics portfolio across multiple 45-day release cycles.
Oversee concurrent data science workstreams ensuring measurable business impact and delivery risk management.
Set architectural direction for AI/ML platforms on AWS including MLOps, cost management, and governance frameworks.
Master's or PhD in Data Science, Statistics, Computer Science, Operations Research, or related field or equivalent experience.
10+ years experience delivering data science/ML/analytics solutions with leadership at portfolio or platform level.
Deep expertise in modeling approaches (statistical, ML, optimization, simulation, GenAI) and evaluation metrics tied to business KPIs.
Extensive hands-on and architectural experience with AWS AI/ML platforms and MLOps practices at scale.
Senior technical leader comfortable managing multiple teams and release cycles in an agile environment.
Strong strategic thinker with experience balancing model performance, explainability, compliance, and cost in regulated contexts.
Experienced in setting data science governance, synthetic data strategy, offline experimentation, and stakeholder communication at executive level.