How to translate academic CVs into industry resumes for research scientist, ML engineer, and applied science roles.
An academic CV lists everything -- every paper, presentation, and award in full citation format.
An industry resume is a 1-2 page sales document. It answers: Why should we hire you for this specific role?
| Academic CV | Industry Resume |
|---|---|
| Full paper citations | "Published 6 peer-reviewed papers in NeurIPS, ICML, ACL" |
| Advisor listed as PI | "Led research project as primary investigator" |
| Teaching assistant | "Delivered instruction to 120+ students; mentored 8 junior researchers" |
| Conference presentations | "Presented research at NeurIPS 2025 -- top 1% acceptance rate" |
1. Summary -- 2-3 sentences: domain expertise + publication record + target role
2. Research Experience -- PhD + postdoc/internships, framed as projects with impact
3. Publications -- condensed (venue + count, not full citations)
4. Skills -- programming languages, frameworks (PyTorch, JAX, TensorFlow), cloud, statistical methods
5. Education -- PhD, thesis title (one sentence)
"Developed novel data augmentation technique for low-resource NLP -- method reduced labeled data requirement by 60%, directly applicable to low-resource language markets (200M+ speakers)."
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Publications
6 peer-reviewed papers | NeurIPS (2), ICML (2), EMNLP (1), ACL (1)
h-index: 8 | 340+ citations (Google Scholar)
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Research Scientist: Novel research, publications valued, more freedom to explore.
Applied Scientist (Amazon): Research applied to products, outcome-focused.
ML Engineer: Model deployment, MLOps, scale.
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