A stochastic integer-programming (SIP) model is presented to optimize long-term scheduling of underground mine operations while considering geological uncertainty. To integrate this uncertainty, a set of stochastic simulations is generated, corresponding to representations of the deposit, and is used as primary inputs to optimization. The two-stage SIP model developed considers a variable cut-off grade and accounts for maximum development, material handling flow conservation, mill and mine capacity, and activity precedencies for an underground nickel mine. The results show that the schedule generated has a higher expected value when considering and managing grade risk. They also demonstrate the benefits of risk control, which this approach allows.