Tommy Tang, Director of Computational Biology at Immunitas Therapeutics, shares his career journey from a low-income childhood in China to leading computational biology at a cancer immunotherapy company. He describes how he self-taught computational skills during his PhD, progressed through postdocs at MD Anderson and Harvard, and eventually led NIH-funded cancer immunology data projects at Dana-Farber. At Immunitas, he uses single-cell RNA sequencing, TCR sequencing, and machine learning methods like logistic regression and random forests on Google Cloud to identify new therapeutic targets for cancer. He also discusses the biology of T-cell expansion, PD-1 immune checkpoints, and the challenges of cell type annotation in single-cell data. He closes with advice on learning meta-skills: read, watch tutorials, apply to real problems, and teach others.