This paper examines the uncapacitated stochastic lot-sizing problem with quantity discounts in finite horizon. By modeling the problem with a scenario tree, we characterize properties of the optimal policy and propose a polynomial time algorithm in terms of the number of nodes in the scenario tree. Numerical experiments are conducted to evaluate the performance of the algorithm and to gain the management insights.