Aanya Iyer
Aanya Iyer's Holland Code
Hand-rendered SVG · 6 dimensions, scored 0–100.
top 3 → RIS
Student vs cohort mean
Aanya Iyer · Cohort mean
Aanya Iyer presents a strong and well-rounded aptitude profile, with particularly high scores in abstract reasoning (91), verbal ability (89), and numeric reasoning (86). Her RIASEC profile — led by Realistic, Investigative, and Social orientations — points toward careers that blend hands-on problem-solving with analytical depth and human interaction. Career match scores place Software Engineering, AI/ML Engineering, and Dentistry at the top, all clustering around a 70–71% fit, suggesting Aanya has genuine flexibility across technical fields rather than a single obvious path.
Across sessions, data science has emerged as a consistent area of curiosity, and the counsellor framework of interest, aptitude, and market demand was applied to help Aanya evaluate her options [1]. Notably, the consolidated career review flagged architecture as a top pathway, described as "consistent across RIASEC, DAT V, and self-report interest," which is worth revisiting even if it sits outside the current match rankings [2]. Her spatial score of 83 lends credibility to that architectural interest and should not be dismissed.
A key sticking point remains stream selection between Science and Commerce, a tension that has surfaced in family conversations and deserves early resolution [2]. On the assessment side, Aanya's mock CET performance was strong overall — Maths 89, English 94 — though "accuracy on the data interpretation section is the gap," and targeted practice on DI sets has been recommended [3]. Addressing this specific gap will strengthen her position across both engineering entrance exams and competitive assessments linked to her civil services interest.
Recommended next step: Confirm Science stream selection with the family, arrange the shadow-day at a partner architecture or tech firm as planned, and begin the six-week data interpretation practice sprint before the next term review.
live LLM inference grounded in 3 cited reports + RIASEC/aptitude data
Career fit (ranked)
Review status
Source reports
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