Participate in staff development activities to continuously enhance your teaching skills and subject knowledge. Complete training before start conducting classes.
Foster a positive, inclusive learning environment that encourages student engagement and curiosity
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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