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I started with total US graduates, tried to segment by major and then layered in interest rate for tech jobs.
Break the problem into a supply-side estimate (number of new graduates in relevant fields) and a demand-side estimate (proportion who apply to large tech companies). Use a top-down approach starting with the total number of college graduates, then narrow down by major, interest in tech, and application behavior. State your assumptions clearly and round numbers to make calculations manageable.
Pro tip: Anchor your estimate to a known figure (e.g., ~2 million bachelor's degrees awarded annually in the US) and then adjust for the global context if the question implies worldwide. Also, mention that you'd validate with data from LinkedIn or company career sites if available.
Ask if the estimate is for the US or globally, and define 'large technology companies' (e.g., FAANG or similar). Assume we're estimating for the US first, then scale if needed.
Start with the total number of bachelor's degrees awarded annually in the US (~2 million). Consider that not all are eligible (e.g., international students may need sponsorship), but for simplicity, use the total.
Estimate the proportion of graduates with degrees in computer science, engineering, information systems, or related fields. Assume ~10% of all graduates, so ~200,000.
Not all relevant graduates apply to large tech; some go to startups, grad school, other industries. Assume ~30% apply to at least one large tech company, yielding ~60,000 applicants.
Cross-check with known data: large tech companies hire tens of thousands of interns and new grads annually, and application volumes are much higher. Adjust upward if needed, considering multiple applications per person and global applicants.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.