Lead ML systems for experimentation and insights generation at scale.
Build production machine learning infrastructure that learns from experimental data to generate evidence-backed product insights and support high-stakes decision-making. This end-to-end role spans model development, data pipelines, statistical methods, and user-facing workflows, with emphasis on calibration, uncertainty quantification, and causal rigor. You will partner across product and research teams to turn complex ML capabilities into actionable tools that demonstrably improve organizational learning and product velocity.
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Found at a specialist agency · listed 25 September 2026 · InsideJobs links you to the original posting.