diff --git a/ax/plot/pareto_utils.py b/ax/plot/pareto_utils.py
index 00ccc8fe8c8..a6009705f07 100644
--- a/ax/plot/pareto_utils.py
+++ b/ax/plot/pareto_utils.py
@@ -579,7 +579,7 @@ def _build_new_optimization_config(
 
 
 def infer_reference_point_from_experiment(
-    experiment: Experiment,
+    experiment: Experiment, data: Data
 ) -> List[ObjectiveThreshold]:
     """This functions is a wrapper around ``infer_reference_point`` to find the nadir
     point from the pareto front of an experiment. Aside from converting experiment
@@ -600,7 +600,8 @@ def infer_reference_point_from_experiment(
 
     # Reading experiment data.
     mb_reference = get_tensor_converter_model(
-        experiment=experiment, data=experiment.fetch_data()
+        experiment=experiment,
+        data=data,
     )
     obs_feats, obs_data, _ = _get_modelbridge_training_data(modelbridge=mb_reference)
 
diff --git a/ax/plot/tests/test_pareto_utils.py b/ax/plot/tests/test_pareto_utils.py
index c3cd0a959fa..505185170db 100644
--- a/ax/plot/tests/test_pareto_utils.py
+++ b/ax/plot/tests/test_pareto_utils.py
@@ -248,7 +248,10 @@ def test_infer_reference_point_from_experiment(self) -> None:
             scalarized=False,
             constrained=False,
         )
-        inferred_reference_point = infer_reference_point_from_experiment(experiment)
+        data = experiment.fetch_data()
+        inferred_reference_point = infer_reference_point_from_experiment(
+            experiment, data=data
+        )
         # The nadir point for this experiment is [-0.5, 0.5]. The function actually
         # deducts 0.1*Y_range from each of the objectives. Since the range for each
         # of the objectives is +/-1.5, the inferred reference point would
@@ -265,7 +268,7 @@ def test_infer_reference_point_from_experiment(self) -> None:
             return_value=([], [], [], []),
         ):
             with self.assertRaisesRegex(RuntimeError, "No frontier observations found"):
-                infer_reference_point_from_experiment(experiment)
+                infer_reference_point_from_experiment(experiment, data=data)
 
     def test_constrained_infer_reference_point_from_experiment(self) -> None:
         experiments = []
@@ -290,14 +293,15 @@ def test_constrained_infer_reference_point_from_experiment(self) -> None:
 
         for experiment in experiments:
             # special case logs a warning message.
+            data = experiment.fetch_data()
             if experiment.optimization_config.outcome_constraints[0].bound == 1000.0:
                 with self.assertLogs(logger, "WARNING"):
                     inferred_reference_point = infer_reference_point_from_experiment(
-                        experiment
+                        experiment, data=data
                     )
             else:
                 inferred_reference_point = infer_reference_point_from_experiment(
-                    experiment
+                    experiment, data=data
                 )
             # The nadir point for this experiment is [-0.5, 0.5]. The function actually
             # deducts 0.1*Y_range from each of the objectives. Since the range for each
@@ -377,7 +381,9 @@ def test_infer_reference_point_from_experiment_shuffled_metrics(self) -> None:
                 obj_t_shuffled,
             ),
         ):
-            inferred_reference_point = infer_reference_point_from_experiment(experiment)
+            inferred_reference_point = infer_reference_point_from_experiment(
+                experiment, data=experiment.fetch_data()
+            )
 
             self.assertEqual(inferred_reference_point[0].op, ComparisonOp.LEQ)
             self.assertEqual(inferred_reference_point[0].bound, -0.35)
diff --git a/ax/service/scheduler.py b/ax/service/scheduler.py
index 5e7113f256e..3fcfb8639b2 100644
--- a/ax/service/scheduler.py
+++ b/ax/service/scheduler.py
@@ -450,10 +450,16 @@ def completion_criterion(self) -> Tuple[bool, str]:
                 and len(self.experiment.trials_by_status[TrialStatus.COMPLETED])
                 >= gss.min_trials
             ):
-                # We infer the nadir reference point to be used by the GSS.
-                self.__inferred_reference_point = infer_reference_point_from_experiment(
-                    self.experiment
-                )
+                # only infer reference point if there is data on the experiment.
+                data = self.experiment.fetch_data()
+                if not data.df.empty:
+                    # We infer the nadir reference point to be used by the GSS.
+                    self.__inferred_reference_point = (
+                        infer_reference_point_from_experiment(
+                            self.experiment,
+                            data=data,
+                        )
+                    )
 
             stop_optimization, global_stopping_msg = gss.should_stop_optimization(
                 experiment=self.experiment,
diff --git a/ax/service/tests/scheduler_test_utils.py b/ax/service/tests/scheduler_test_utils.py
index fa4fe4bc110..55d29966520 100644
--- a/ax/service/tests/scheduler_test_utils.py
+++ b/ax/service/tests/scheduler_test_utils.py
@@ -820,6 +820,40 @@ def test_inferring_reference_point(self) -> None:
             scheduler.run_n_trials(max_trials=10)
             mock_infer_rp.assert_called_once()
 
+    def test_inferring_reference_point_no_data(self) -> None:
+        init_test_engine_and_session_factory(force_init=True)
+        experiment = get_branin_experiment_with_multi_objective()
+        experiment.runner = self.runner
+        gs = self._get_generation_strategy_strategy_for_test(
+            experiment=experiment,
+            generation_strategy=self.sobol_GS_no_parallelism,
+        )
+
+        scheduler = Scheduler(
+            experiment=experiment,
+            generation_strategy=gs,
+            options=SchedulerOptions(
+                # Stops the optimization after 5 trials.
+                global_stopping_strategy=DummyGlobalStoppingStrategy(
+                    min_trials=0,
+                    trial_to_stop=5,
+                ),
+            ),
+            db_settings=self.db_settings,
+        )
+        empty_data = Data(
+            df=pd.DataFrame(
+                columns=["metric_name", "arm_name", "trial_index", "mean", "sem"]
+            )
+        )
+        with patch(
+            "ax.service.scheduler.infer_reference_point_from_experiment"
+        ) as mock_infer_rp, patch.object(
+            scheduler.experiment, "fetch_data", return_value=empty_data
+        ):
+            scheduler.run_n_trials(max_trials=1)
+            mock_infer_rp.assert_not_called()
+
     def test_global_stopping(self) -> None:
         gs = self._get_generation_strategy_strategy_for_test(
             experiment=self.branin_experiment,