<p>Career selection is a multi-criteria decision-making problem that can be challenging, especially when uncertainties are involved. To tackle such a problem, several decision-making techniques have been used to compare and rank the alternatives. Pythagorean Fuzzy Sets (PyFS), which are used to describe uncertainty, have also been used by some researchers in attempts to solve decision making applications. This paper introduces PyFS in type-2 Fuzzy Environments as type-2 PyFS (T2PyFS) to handle the uncertainty of a decision making problem more appropriately. Unlike conventional PyFS, T2PyFS incorporates secondary membership functions that capture higher-order uncertainty and hesitation in expert judgments, thereby providing a more realistic and flexible modeling framework. We define several arithmetic operations and algebraic properties related to it, and propose its level sets, we investigate related properties. We also develop the Hamming and Euclidean distance of our T2PyFS, and design three decision making algorithms based on the level sets, max-min-max composition and distance measure. Along the lines of academic performance, we apply the proposed decision making algorithms to quantify and compare the different criteria and alternatives systematically. Finally, we conclude this study with a comparative analysis of the proposed algorithms.</p>