diff --git a/src/mavedb/lib/mave/utils.py b/src/mavedb/lib/mave/utils.py
index f59a3fca0..dd6b75916 100644
--- a/src/mavedb/lib/mave/utils.py
+++ b/src/mavedb/lib/mave/utils.py
@@ -1,5 +1,7 @@
 import re
 
+import pandas as pd
+
 NA_VALUE = "NA"
 
 NULL_VALUES = ("", "na", "nan", "nil", "none", "null", "n/a", "undefined", NA_VALUE)
@@ -22,6 +24,9 @@
 
 def is_csv_null(value):
     """Return True if a string from a CSV file represents a NULL value."""
+    # Avoid any boolean miscasts from comparisons by handling NA types up front.
+    if pd.isna(value):
+        return True
     # Number 0 is treated as False so that all 0 will be converted to NA value.
     if value == 0:
         return value
diff --git a/src/mavedb/routers/score_sets.py b/src/mavedb/routers/score_sets.py
index 24c602ca6..44fd2a307 100644
--- a/src/mavedb/routers/score_sets.py
+++ b/src/mavedb/routers/score_sets.py
@@ -854,9 +854,13 @@ async def update_score_set(
             scores_data = pd.DataFrame(
                 variants_to_csv_rows(item.variants, columns=score_columns, dtype="score_data")
             ).replace("NA", pd.NA)
-            count_data = pd.DataFrame(
-                variants_to_csv_rows(item.variants, columns=count_columns, dtype="count_data")
-            ).replace("NA", pd.NA)
+
+            if item.dataset_columns["count_columns"]:
+                count_data = pd.DataFrame(
+                    variants_to_csv_rows(item.variants, columns=count_columns, dtype="count_data")
+                ).replace("NA", pd.NA)
+            else:
+                count_data = None
 
             # Although this is also updated within the variant creation job, update it here
             # as well so that we can display the proper UI components (queue invocation delay