The　employment　situation　of　graduates　can　directly　reflect　the　quality　of　talent　training　and　social　recognition　of　the　school.　Based　on　the　big　data　analysis　method,　learning　a　graduate　employment　evaluation　model　to　predict　and　guide　the　employment　of　students　in　the　school.　This　way　not　only　will　improve　the　employment　success　rate　of　graduates　but　also　will　improve　the　talent　training　ability　of　universities.　This　paper　collects　the　employment　information　of　graduates　from　a　university　in　Beijing　in　the　past　three　years.　We　use　the　Analytic　Hierarchy　Process　to　establish　an　employment　evaluation　model.　more　importantly,　we　learn　the　student　ability　distribution　in　an　unsupervised　manner,　i.e.,　without　a　need　of　annotating　records.　The　experiment　shows　this　manner　has　some　advantage　in　extreme　ratings.　In　addition,　we　select　fresh　graduates　who　volunteer　to　participate　in　the　experiment　for　verification.　The　college　counselor　establishes　one-on-one　employment　guidance　with　students　with　low　employability　scores.　The　final　results　show　that　the　method　has　achieved　a　good　performance,　and　the　employment　rate　of　graduates　participating　in　the　experiment　reaches　100%.　Therefore,　this　method　can　provide　an　effective　reference　for　the　employment　guidance　and　evaluation　of　the　university.　©　2020　by　the　authors.