MS in bioinformatics / DS → industry: the AI-augmented job-search workflow
Most job-search advice for MS graduates was written for two audiences: undergraduates with no specialization, or PhDs with publication portfolios. Neither set of advice fits you cleanly, which is why following it generically returns ambiguous results.
This is the working sequence I’d run if I were you, with the AI-augmentation layer baked in from week one — not as a productivity tip but as a load-bearing component. You do not have time to do this the slow way.
Days 1–14: audit and translate
Inventory every project, paper, internship, and TA role from the last three years. For each, write a single sentence answering: what was the deliverable, what was your specific contribution, and what would have failed without you. Use a Claude Skill or workflow to draft initial language; rewrite by hand. AI gives you the scaffold; the specificity has to be yours, because that specificity is the differentiator a recruiter will see in twelve seconds.
Days 15–35: positioning and portfolio
Pick exactly two role tracks (e.g., applied ML engineer + computational biologist). Three is too many; one is too narrow. Then build one demonstration artifact per track — a working pipeline, a notebook, a small open-source tool, a written analysis — that a hiring manager can evaluate in under fifteen minutes without your help. The artifact is the proof. The resume is the index.
Days 36–60: outbound, with friction removed
Pre-write three cold-email templates for three role contexts. Use AI to scale variations within those templates, never to generate the message from scratch. Send forty per week to a curated list of hiring managers two levels above the role you want — not recruiters. The volume is real and unglamorous. Most candidates skip this step, which is why most candidates do not get interviews.
Days 61–90: interviews
Practice case interviews against an LLM playing a hostile interviewer, not an encouraging one. The model is good at being technically pedantic in a way that mirrors a senior engineer’s failure modes. Run the same case three times until you can answer cleanly. Track which classes of question you keep losing on, and fix the underlying gap, not the symptom.
This is the working sequence. The rest of the site is the toolbox.