  We consider the problem of job assignment where a master server aims to
compute some tasks and is provided a few child servers to compute under a
uniform straggling pattern where each server is equally likely to straggle. We
distribute tasks to the servers so that the master is able to receive most of
the tasks even if a significant number of child servers fail to communicate. We
first show that all \textit{balanced} assignment schemes have the same
expectation on the number of distinct tasks received and then study the
variance. The variance or the second moment is a useful metric to study as
there could be a high \textit{variation} in the number of distinct tasks
received. We show constructions using a generalization of ``Balanced Incomplete
Block Design'' [11,40] minimizes the variance, and constructions based on
repetition coding schemes attain the largest variance. Both minimum variance
and maximum variance attaining designs have their own use cases depending on
whether the master aims for a heavy-tailed or light-tailed distribution on the
number of distinct jobs. We further show the equivalence between job and
server-based assignment schemes when the number of jobs and child servers are
equal.
