What You’ll Do
- Process DDTM/translational medicine literature screening, entity extraction, relationship judgment, evidence capture, and field completion.
- Evaluate relationships among drugs, diseases, targets, biomarkers, clinical evidence, and translational evidence.
- Create positive examples, negative examples, edge cases, and historical error samples for AI workflow evaluation.
- Help define DDTM fields, quality thresholds, review rules, and migration acceptance criteria.
- Partner with the AI Native Data Engineer to convert manual decisions into Skills, prompts, rules, QA checklists, and error loops.
What We’re Looking For
- Bachelor's degree or above in Life Sciences, Biomedical Sciences, Pharmacy, Bioinformatics, or a related field.
- 2+ years in life sciences content, drug R&D intelligence, clinical research, biomedical literature curation, or medical database work.
- Able to read English biomedical literature and understand drugs, diseases, targets, biomarkers, clinical stages, and evidence levels.
- Experience with DDTM, translational medicine, drug intelligence, clinical evidence, or biomedical databases preferred.
- Detail-oriented and comfortable working through backlog while documenting repeatable rules.
- Willing to use AI tools while owning the scientific/content judgment.
- Chinese-English collaboration ability preferred.
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