diff --git a/xgboost_ray/data_sources/modin.py b/xgboost_ray/data_sources/modin.py
index 1f2f1f57..78e229c7 100644
--- a/xgboost_ray/data_sources/modin.py
+++ b/xgboost_ray/data_sources/modin.py
@@ -16,6 +16,13 @@
     import modin  # noqa: F401
     from modin.config.envvars import Engine
     from packaging.version import Version
+    from modin.pandas import (  # noqa: F401
+        DataFrame as ModinDataFrame,  # noqa: F401
+        Series as ModinSeries  # noqa: F401
+    )
+    from modin.distributed.dataframe.pandas import (  # noqa: F401
+        unwrap_partitions  # noqa: F401
+    )
     MODIN_INSTALLED = Version(modin.__version__) >= Version("0.9.0")
 
     # Check if importing the Ray engine leads to errors
@@ -29,8 +36,11 @@ def _assert_modin_installed():
     if not MODIN_INSTALLED:
         raise RuntimeError(
             "Tried to use Modin as a data source, but modin is not "
-            "installed. This function shouldn't have been called. "
-            "\nFIX THIS by installing modin: `pip install modin`. "
+            "installed or it conflicts with the pandas version. "
+            "This function shouldn't have been called. "
+            "\nFIX THIS by installing modin: `pip install modin` "
+            "and making sure that the installed pandas version is "
+            "supported by modin."
             "\nPlease also raise an issue on our GitHub: "
             "https://github.com/ray-project/xgboost_ray as this part of "
             "the code should not have been reached.")
@@ -53,8 +63,11 @@ def is_data_type(data: Any,
                      filetype: Optional[RayFileType] = None) -> bool:
         if not MODIN_INSTALLED:
             return False
-        from modin.pandas import DataFrame as ModinDataFrame, \
-            Series as ModinSeries
+        # Has to be imported again.
+        from modin.pandas import (  # noqa: F811
+            DataFrame as ModinDataFrame,  # noqa: F811
+            Series as ModinSeries  # noqa: F811
+        )
 
         return isinstance(data, (ModinDataFrame, ModinSeries))
 
@@ -87,8 +100,11 @@ def load_data(
     @staticmethod
     def convert_to_series(data: Any) -> pd.Series:
         _assert_modin_installed()
-        from modin.pandas import DataFrame as ModinDataFrame, \
-            Series as ModinSeries
+        # Has to be imported again.
+        from modin.pandas import (  # noqa: F811
+            DataFrame as ModinDataFrame,  # noqa: F811
+            Series as ModinSeries  # noqa: F811
+        )
 
         if isinstance(data, ModinDataFrame):
             return pd.Series(data._to_pandas().squeeze())
@@ -104,7 +120,10 @@ def get_actor_shards(
             Tuple[Any, Optional[Dict[int, Any]]]:
         _assert_modin_installed()
 
-        from modin.distributed.dataframe.pandas import unwrap_partitions
+        # Has to be imported again.
+        from modin.distributed.dataframe.pandas import (  # noqa: F811
+            unwrap_partitions  # noqa: F811
+        )
 
         actor_rank_ips = get_actor_rank_ips(actors)