The origin of Ultra-High-Energy Cosmic Rays (UHECRs) is one of the biggest mysteries in
modern astrophysics. Since UHECRs are deflected by Galactic and extragalactic magnetic fields,
their arrival directions do not point to their sources. Previous analyses conducted on the arrival
directions of high-energy events ($𝐸 ≥ 32\,\text{EeV}$) recorded by the Surface Detector of the Pierre
Auger Observatory have not shown significant anisotropies. The largest excess found in the first
19 years of data - at the $4.0\,\sigma$ level - is in the region around Centaurus A, and it is also the driving
force of a correlation of UHECR arrival directions with a catalog of Starburst Galaxies, which
is at the $3.8\,\sigma$ level. Since UHECRs are mostly nuclei, the lightest ones (least charged) are also
the least deflected. While the mass of the events can be estimated better using the Fluorescence
Detector of the Pierre Auger Observatory, the Surface Detector provides the necessary statistics
needed for astrophysical studies. The introduction of novel mass-estimation techniques, such as
machine learning models and an algorithm based on air-shower universality, will help identify
high-rigidity events in the Surface Detector data of the Pierre Auger Observatory. With this work,
we present how event-per-event mass estimators can help enhance the sensitivity in the search for
anisotropies in the arrival directions of UHECRs at small and intermediate angular scales using
simulations.