Aarav Sharma
Aarav Sharma's Holland Code
Hand-rendered SVG · 6 dimensions, scored 0–100.
top 3 → REC
Student vs cohort mean
Aarav Sharma · Cohort mean
Aarav Sharma presents a well-defined aptitude and interest profile that points toward structured, hands-on, and leadership-oriented career paths. His strongest cognitive scores are in verbal reasoning (82) and speed-accuracy (72), with solid mechanical (64) and spatial (62) abilities rounding out a practically oriented skill set. Numeric aptitude (43) is the one area that sits below the midrange, which is worth keeping in mind when considering fields that demand heavy quantitative analysis.
His RIASEC profile is led by Realistic, Enterprising, and Conventional tendencies (REC), reflecting a preference for concrete problem-solving, goal-directed activity, and organized work environments. This combination aligns naturally with careers that blend technical execution with leadership responsibility — qualities that show up clearly in his top three matches: Chartered Accountant (fit 76), Civil Engineer (fit 74), and Armed Forces Officer (fit 74). It is encouraging that two of these matches span different families, suggesting Aarav has genuine flexibility in direction rather than a narrow fit.
Civil Engineering and the Armed Forces track deserve particular attention given his strong spatial, mechanical, and Realistic-Enterprising scores. The Armed Forces Officer path also leverages his verbal strength and leadership orientation, while Civil Engineering maps well onto his spatial and mechanical aptitudes. Chartered Accountancy, though ranked first by overall fit, would benefit from deliberate work on numeric skills before Aarav fully commits to that route.
At this stage, Aarav should be encouraged to explore each option experientially rather than deciding too early. Recommended next step: arrange informational conversations or shadowing opportunities with professionals in Civil Engineering and the Armed Forces so Aarav can ground his decision in real-world exposure.
live LLM inference grounded in 0 cited reports + RIASEC/aptitude data
Career fit (ranked)
Review status
Source reports
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