Identify the critical cost area and propose cost improvement to business units.
Evaluating previous budgets and expenditures to develop and implement future budgets.
Liaise with business units to provide insights into performance and efficiency to facilitate achievement of departmental Key Performance Indicators (KPI).
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Build and operate the harder engineering layers of a solution when projects demand it: orchestrated pipelines, worker-based and event-driven architectures, stream processing, and scaling for data volume and concurrency.
Own solution quality: data validation, model evaluation, reproducibility, performance, and operational reliability (monitoring, alerting, failure recovery).
Lead and mentor a team of junior data scientists and analysts; review their work, unblock them technically, and grow their skills.
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