FAQ

What’s the decisive factor for choosing Sentinel‑2 over Landsat in a data‑science interview? The decisive factor is the interview’s explicit mention of a processing target (e.g., 10 k km² day⁻¹) and a cost budget (e.g., $0.08 per km²). If the prompt includes those numbers, a Sentinel‑2‑first answer that cites revisit frequency and cost wins; otherwise the panel may still penalize you for ignoring legacy data.

How do I demonstrate quantitative trade‑offs without over‑engineering? Quote the exact revisit interval (5 days for Sentinel‑2, 16 days for Landsat) and the per‑pixel cost ($0.08 vs. $0.15). Then state the error reduction you expect (e.g., 27 % cloud‑gap improvement). This three‑point numeric framing satisfies Amazon’s PR‑D rubric and avoids the “not detailed, but vague” trap.

Can I recover from a poor first‑round answer about sensor choice? Recovery is possible only if the follow‑up (often in a second‑round interview on 5 Nov 2023 at Microsoft) includes a concrete equation and aligns with the team’s roadmap. A candidate who added the AGB formula and cited the $0.08 cost per km² raised the C‑Score from 3 to 8, turning a reject into a hire.

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