diff --git a/freqtrade/data/dataprovider.py b/freqtrade/data/dataprovider.py
index e639b3ae7..c6519d2b8 100644
--- a/freqtrade/data/dataprovider.py
+++ b/freqtrade/data/dataprovider.py
@@ -196,7 +196,9 @@ class DataProvider:
         Clear pair dataframe cache.
         """
         self.__cached_pairs = {}
-        self.__cached_pairs_backtesting = {}
+        # Don't reset backtesting pairs -
+        # otherwise they're reloaded each time during hyperopt due to with analyze_per_epoch
+        # self.__cached_pairs_backtesting = {}
         self.__slice_index = 0
 
     # Exchange functions
diff --git a/freqtrade/optimize/hyperopt.py b/freqtrade/optimize/hyperopt.py
index 76fc84609..f15e0b7d8 100644
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -580,11 +580,23 @@ class Hyperopt:
                     max_value=self.total_epochs, redirect_stdout=False, redirect_stderr=False,
                     widgets=widgets
                 ) as pbar:
-                    EVALS = ceil(self.total_epochs / jobs)
-                    for i in range(EVALS):
+                    start = 0
+
+                    if self.analyze_per_epoch:
+                        # First analysis not in parallel mode when using --analyze-per-epoch.
+                        # This allows dataprovider to load it's informative cache.
+                        asked, is_random = self.get_asked_points(n_points=1)
+                        f_val0 = self.generate_optimizer(asked[0])
+                        self.opt.tell(asked, [f_val0['loss']])
+                        self.evaluate_result(f_val0, 1, is_random[0])
+                        pbar.update(1)
+                        start += 1
+
+                    evals = ceil((self.total_epochs - start) / jobs)
+                    for i in range(evals):
                         # Correct the number of epochs to be processed for the last
                         # iteration (should not exceed self.total_epochs in total)
-                        n_rest = (i + 1) * jobs - self.total_epochs
+                        n_rest = (i + 1) * jobs - (self.total_epochs - start)
                         current_jobs = jobs - n_rest if n_rest > 0 else jobs
 
                         asked, is_random = self.get_asked_points(n_points=current_jobs)
@@ -594,7 +606,7 @@ class Hyperopt:
                         # Calculate progressbar outputs
                         for j, val in enumerate(f_val):
                             # Use human-friendly indexes here (starting from 1)
-                            current = i * jobs + j + 1
+                            current = i * jobs + j + 1 + start
 
                             self.evaluate_result(val, current, is_random[j])
 
diff --git a/tests/optimize/test_hyperopt.py b/tests/optimize/test_hyperopt.py
index 0f615b7a3..eaea8aee7 100644
--- a/tests/optimize/test_hyperopt.py
+++ b/tests/optimize/test_hyperopt.py
@@ -922,6 +922,45 @@ def test_in_strategy_auto_hyperopt_with_parallel(mocker, hyperopt_conf, tmpdir,
     hyperopt.start()
 
 
+def test_in_strategy_auto_hyperopt_per_epoch(mocker, hyperopt_conf, tmpdir, fee) -> None:
+    patch_exchange(mocker)
+    mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
+    (Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
+
+    hyperopt_conf.update({
+        'strategy': 'HyperoptableStrategy',
+        'user_data_dir': Path(tmpdir),
+        'hyperopt_random_state': 42,
+        'spaces': ['all'],
+        'epochs': 3,
+        'analyze_per_epoch': True,
+    })
+    go = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.generate_optimizer',
+                      return_value={
+                            'loss': 0.05,
+                            'results_explanation': 'foo result', 'params': {},
+                            'results_metrics': generate_result_metrics(),
+                        })
+    hyperopt = Hyperopt(hyperopt_conf)
+    hyperopt.backtesting.exchange.get_max_leverage = MagicMock(return_value=1.0)
+    assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
+    assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)
+    assert hyperopt.backtesting.strategy.bot_loop_started is True
+
+    assert hyperopt.backtesting.strategy.buy_rsi.in_space is True
+    assert hyperopt.backtesting.strategy.buy_rsi.value == 35
+    assert hyperopt.backtesting.strategy.sell_rsi.value == 74
+    assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value == 30
+    buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range
+    assert isinstance(buy_rsi_range, range)
+    # Range from 0 - 50 (inclusive)
+    assert len(list(buy_rsi_range)) == 51
+
+    hyperopt.start()
+    # backtesting should be called 3 times (once per epoch)
+    assert go.call_count == 3
+
+
 def test_SKDecimal():
     space = SKDecimal(1, 2, decimals=2)
     assert 1.5 in space