Model approval rate doubles overnight
An ops alert fires: your loan-approval model's approval rate jumped from 22% to 61% in two hours with no model change. Dashboards: the model serves 200s, latency normal. Digging in, the feature 'annual_income' is now arriving as 0 or null for ~70% of applicants since 13:00, and the model treats low/zero income with a feature default that happens to push scores toward approval. An upstream data provider changed a JSON field name ('income' → 'incomeAnnual') in a 13:00 release, so your ingestion silently maps the old key to null. Triage and respond.
What a strong answer looks like
Stop the bleeding first (mitigate), then form hypotheses from real signals. Separate root cause from symptom, communicate status as you go, and close with what prevents a repeat.
0:00 of about 35 min
Which questions mattered is sealed until you submit. Telling you now would just be handing over the edge cases.
Run or narrate your approach, then ask the coach.