In this study, an analysis pipeline is established and implemented on a high-content, siRNA-based genetic screen in human Hep3B cells to identify novel regulators of key hepatocyte traits using a multi-parametric phenotypic profiling approach. Cell count, lipid droplet count, and ASGR1 area were extracted from high-content images of 576 candidates. Mahalanobis distance is used to rank and select 98 hits which were clustered into 8 phenotypes. Priority candidates were sequenced, identifying 26 genes linked to ASGR1 expression, lipid metabolism, and liver cancer cell viability. Gene Ontology enrichment analysis associated clusters with processes like stress response and mitochondrial organization that influence the observed phenotypes. Notably, candidates in cluster 1 may play a role in modulating ASGR1 and seem to be associated with cellular response to starvation. Candidate genes in cluster 5 seem to be associated with chaperones and protein folding and their knockdown appears to be most effective for inducing lipid droplet biogenesis. Meanwhile two genes highly expressed in a variety of cancers, FN1 and HNRNPC, also pop out. This comprehensive screening workflow provided new avenues of research for insight into the complex network controlling hepatocyte health, ASGR1 regulation, and lipid droplet formation.