We consider a stochastic differential equation and its Euler-Maruyama (EM) scheme, under some appropriate conditions, they both admit a unique invariant measure, denoted by π and π η respectively (η is the step size of the EM scheme). We construct an empirical measure η of the EM scheme as a statistic of π η , and use Stein's method developed in Fang, Shao and Xu (Probab. Theory Related Fields 174 (2019) 945-979) to prove a central limit theorem of η . The proof of the self-normalized Cramér-type moderate deviation (SNCMD) is based on a standard decomposition on Markov chain, splitting η −1/2 ( η (.) − π(.)) into a martingale difference series sum H η and a negligible remainder R η . We handle H η by the time-change technique for martingale, while prove that R η is exponentially negligible by concentration inequalities, which have their independent interest. Moreover, we show that SNCMD holds for x = o(η −1/6 ), which has the same order as that of the classical result in Shao (J.