diff --git a/ingestion/src/metadata/pii/ner_scanner.py b/ingestion/src/metadata/pii/ner_scanner.py
index 9d9b7a9319b..6fe3644b966 100644
--- a/ingestion/src/metadata/pii/ner_scanner.py
+++ b/ingestion/src/metadata/pii/ner_scanner.py
@@ -48,20 +48,23 @@ class NERScanner:
     Based on https://microsoft.github.io/presidio/
     """
 
-    import spacy
-    from presidio_analyzer import AnalyzerEngine
-    from presidio_analyzer.nlp_engine.spacy_nlp_engine import SpacyNlpEngine
+    def __init__(self):
+        import spacy
+        from presidio_analyzer import AnalyzerEngine
+        from presidio_analyzer.nlp_engine.spacy_nlp_engine import SpacyNlpEngine
 
-    try:
-        spacy.load(SPACY_EN_MODEL)
-    except OSError:
-        logger.warning("Downloading en_core_web_md language model for the spaCy")
-        from spacy.cli import download
+        try:
+            spacy.load(SPACY_EN_MODEL)
+        except OSError:
+            logger.warning("Downloading en_core_web_md language model for the spaCy")
+            from spacy.cli import download
 
-        download(SPACY_EN_MODEL)
-        spacy.load(SPACY_EN_MODEL)
+            download(SPACY_EN_MODEL)
+            spacy.load(SPACY_EN_MODEL)
 
-    analyzer = AnalyzerEngine(nlp_engine=SpacyNlpEngine(models={"en": SPACY_EN_MODEL}))
+        self.analyzer = AnalyzerEngine(
+            nlp_engine=SpacyNlpEngine(models={"en": SPACY_EN_MODEL})
+        )
 
     @staticmethod
     def get_highest_score_label(
@@ -77,8 +80,7 @@ class NERScanner:
                 most_used_label_occurrence = score[1]
         return label_score or (None, None)
 
-    @classmethod
-    def scan(cls, sample_data_rows: List[Any]) -> Optional[TagAndConfidence]:
+    def scan(self, sample_data_rows: List[Any]) -> Optional[TagAndConfidence]:
         """
         Scan the column's sample data rows and look for PII
         """
@@ -87,7 +89,7 @@ class NERScanner:
         str_sample_data_rows = [str(row) for row in sample_data_rows if row is not None]
         for row in str_sample_data_rows:
             try:
-                results = cls.analyzer.analyze(row, language="en")
+                results = self.analyzer.analyze(row, language="en")
                 for result in results:
                     logger.debug("Found %s", result.entity_type)
                     tag = result.entity_type
@@ -104,7 +106,7 @@ class NERScanner:
                 logger.warning(f"Unknown error while processing {row} - {exc}")
                 logger.debug(traceback.format_exc())
 
-        label, score = cls.get_highest_score_label(labels_score, str_sample_data_rows)
+        label, score = self.get_highest_score_label(labels_score, str_sample_data_rows)
         if label and score:
             tag_type = NEREntity.__members__.get(label, TagType.NONSENSITIVE).value
             return TagAndConfidence(tag=tag_type, confidence=score)
diff --git a/ingestion/src/metadata/pii/processor.py b/ingestion/src/metadata/pii/processor.py
index dc9af90a8be..46cb68d1f09 100644
--- a/ingestion/src/metadata/pii/processor.py
+++ b/ingestion/src/metadata/pii/processor.py
@@ -34,6 +34,7 @@ class PIIProcessor:
     def __init__(self, metadata: OpenMetadata):
 
         self.metadata = metadata
+        self.ner_scanner = NERScanner()
 
     def patch_column_tag(
         self, tag_type: str, table_entity: Table, column_name: str
@@ -81,7 +82,7 @@ class PIIProcessor:
 
             # Scan by column name. If no results there, check the sample data, if any
             tag_and_confidence = ColumnNameScanner.scan(column.name.__root__) or (
-                NERScanner.scan([row[idx] for row in table_data.rows])
+                self.ner_scanner.scan([row[idx] for row in table_data.rows])
                 if table_data
                 else None
             )
diff --git a/ingestion/tests/unit/pii/test_ner_scanner.py b/ingestion/tests/unit/pii/test_ner_scanner.py
index ed4b6256eae..569f0fe3df0 100644
--- a/ingestion/tests/unit/pii/test_ner_scanner.py
+++ b/ingestion/tests/unit/pii/test_ner_scanner.py
@@ -22,10 +22,12 @@ class NERScannerTest(TestCase):
     Validate various typical column names
     """
 
+    ner_scanner = NERScanner()
+
     def test_scanner_none(self):
-        self.assertIsNone(NERScanner.scan(list(range(100))))
+        self.assertIsNone(self.ner_scanner.scan(list(range(100))))
         self.assertIsNone(
-            NERScanner.scan(
+            self.ner_scanner.scan(
                 " ".split(
                     "Lorem ipsum dolor sit amet, consectetur adipiscing elit. Nam consequat quam sagittis convallis cursus."
                 )
@@ -34,7 +36,7 @@ class NERScannerTest(TestCase):
 
     def test_scanner_sensitive(self):
         self.assertEqual(
-            NERScanner.scan(
+            self.ner_scanner.scan(
                 [
                     "geraldc@gmail.com",
                     "saratimithi@godesign.com",
@@ -44,6 +46,8 @@ class NERScannerTest(TestCase):
             TagType.SENSITIVE,
         )
         self.assertEqual(
-            NERScanner.scan(["im ok", "saratimithi@godesign.com", "not sensitive"]).tag,
+            self.ner_scanner.scan(
+                ["im ok", "saratimithi@godesign.com", "not sensitive"]
+            ).tag,
             TagType.SENSITIVE,
         )