Remote-controlled humanoid robots can revolutionize manufacturing, construction, and healthcare industries by performing complex or dangerous manual tasks traditionally done by humans. We refer to these behaviors as Dynamic Loco-Manipulation (DLM). To successfully complete these tasks, humans control the position of their bodies and contact forces at their hands. To enable similar whole-body control in humanoids, we introduce loco-manipulation retargeting strategies with switched position and force control modes in a bilateral teleoperation framework. Our proposed locomotion mappings use the pitch and yaw of the operator's torso to control robot position or acceleration. The manipulation retargeting maps the operator's arm movements to the robot's arms for joint-position or impedance control of the end-effector. A Human-Machine Interface captures the teleoperator's motion and provides haptic feedback to their torso, enhancing their awareness of the robot's interactions with the environment. In this paper, we demonstrate two forms of DLM. First, we show the robot slotting heavy boxes (5-10.5 kg), weighing up to 83% of the robot's weight, into desired positions. Second, we show human-robot collaboration for carrying an object, where the robot and teleoperator take on leader and follower roles.