diff --git a/pandas/core/groupby/groupby.py b/pandas/core/groupby/groupby.py
index 9c695148a75c0..97f49eabcc5c3 100644
--- a/pandas/core/groupby/groupby.py
+++ b/pandas/core/groupby/groupby.py
@@ -2896,7 +2896,7 @@ def _get_cythonized_result(
         grouper = self.grouper
 
         ids, _, ngroups = grouper.group_info
-        output: dict[base.OutputKey, np.ndarray] = {}
+        output: dict[base.OutputKey, ArrayLike] = {}
 
         base_func = getattr(libgroupby, how)
         base_func = partial(base_func, labels=ids)
@@ -2911,6 +2911,7 @@ def blk_func(values: ArrayLike) -> ArrayLike:
             else:
                 result_sz = len(values)
 
+            result: ArrayLike
             result = np.zeros(result_sz, dtype=cython_dtype)
             if needs_2d:
                 result = result.reshape((-1, 1))
diff --git a/pandas/core/reshape/tile.py b/pandas/core/reshape/tile.py
index c5d06bcef72a4..656d38a50f77f 100644
--- a/pandas/core/reshape/tile.py
+++ b/pandas/core/reshape/tile.py
@@ -418,7 +418,11 @@ def _bins_to_cuts(
             bins = unique_bins
 
     side = "left" if right else "right"
-    ids = ensure_platform_int(bins.searchsorted(x, side=side))
+    # error: No overload variant of "searchsorted" of "ndarray" matches
+    # argument types "Any", "str"
+    ids = ensure_platform_int(
+        bins.searchsorted(x, side=side)  # type: ignore[call-overload]
+    )
 
     if include_lowest:
         ids[np.asarray(x) == bins[0]] = 1