Data Modeling
Mathematical and Computational Data Modeling
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Volume 6 Number 1 2025
RESEARCH ARTICLE (Open Access)
Personality-Informed Recruitment for Technical Teams: A Practical Application of the Myers-Briggs Type Indicator (MBTI)
Md. Mahfujul Alam 1*
Data Modeling 6 (1) 1-10 https://doi.org/10.25163/data.6110855
Submitted: 24 March 2025 Revised: 17 May 2025 Accepted: 26 May 2025 Published: 28 May 2025
Abstract
Recruitment for technical teams still leans, more often than not, on credentials and skills tests — a sensible starting point, perhaps, but one that says little about whether a candidate will actually work well alongside the people already in the room. This study set out to explore whether the Myers-Briggs Type Indicator (MBTI) could offer something more: a practical, if imperfect, lens for aligning candidates with roles based on cognitive-function fit rather than resume alone. Fifteen employees across an existing technical department's hierarchy — from Head of Department down to Junior Executive — completed MBTI assessments, and their results were compared against a reference population of 1,439 personality-labeled records drawn from a public dataset. A rule-based classification pipeline, built in Python and grounded in established cognitive-function and team-effectiveness literature, mapped candidates onto four broad role categories, isolating 879 records meeting an "ideal" configuration for benchmarking purposes. The comparison revealed a fairly uneven deviation between the department's current composition and this ideal distribution, with some MBTI types considerably underrepresented relative to expectation. From this, role-specific personality profiles were generated to guide future recruitment and internal development decisions. Taken together, the findings suggest that MBTI, applied carefully and not in isolation, may offer HR practitioners a workable heuristic for improving role-fit within technical teams — though the small organizational sample and the reliance on a non-proprietary assessment platform mean these results should be treated as a starting point rather than a settled conclusion.
Keywords: Myers-Briggs Type Indicator; technical recruitment; team composition; cognitive functions; human resource management
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