Ovarian cancer remains a disease with high mortality due to late-stage diagnoses and tumor recurrence, demanding studies to define molecular features of the disease that can lead to earlier detection and lower recurrence rates. Cancer stem-like cells (CSCs) have been shown to play roles in tumor initiation, therapy resistance, recurrence, and metastasis in many cancers, including ovarian cancer. Though a controversial hypothesis, the ovarian cancer stem-like cell (OCSC) hierarchy has been proposed to be “pyramid-like” with a multi-potent progenitor at the top of the hierarchy that can divide symmetrically to expand its cell numbers, or asymmetrically into a quiescent state or multiple classes of differentiated cell types. These quiescent OCSCs are proposed to be a reservoir for disease recurrence due to chemoresistance and retaining their multi-potency. Taken together, single-cell characterization of OCSC fate decisions and the molecular landscapes that shape these processes would provide a significant advance in our understanding of tumor initiation, chemoresistance, and recurrence in ovarian cancer. Here, we profiled thousands of single cells from patient-derived cell lines and primary tumors using high-resolution single-cell total RNA-seq (STORM-seq) and inferred lineage fate trajectories using a barcode-free approach. Additionally, we introduce a new multi-omic technology to measure metabolic states of single cells and integrate with single-cell RNA-seq (scRNA-seq). By integration of these two technologies, we uncover new marker genes, changes in relative redox poise, and mitochondrial dynamics associated with lineage fate decisions in OCSCs.