$ cat jobs/pharmacovigilance-expert-micro1-6e4e454c1d66.json
Pharmacovigilance Expert
Role Title: Pharmacovigilance Expert Role Type: Contractor Location: Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety expertise on a key customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. This opportunity is ideal for professionals experienced in authoring and reviewing complex safety reports, passionate about data quality, and committed to clear written and verbal communication. Scope of Work Author and review evaluation tasks based on DSURs, PSURs/PBRERs, and associated safety data and case-level records. Apply expert judgment to assess the accuracy and adequacy of interval safety findings, signal evaluations, and benefit-risk conclusions in alignment with best practices. Assess template and structural conformity to ICH E2F and ICH E2C requirements, including proper section content, presentation of cumulative versus interval data, and completeness of appendices. Reconcile figures and case counts across report sections and data sources, identifying and documenting discrepancies significant for regulatory review. Evaluate safety conclusions in light of new data or events, and provide clear, structured written rationales supporting your determinations. Deliver structured feedback to inform the development of AI-driven tools for pharmacovigilance documentation and analysis. Preferred Qualifications 5+ years of pharmacovigilance or drug safety experience at a sponsor, CRO, or as an independent consultant. Demonstrated proficiency in authoring or reviewing DSURs and/or PSURs/PBRERs from start to finish. Working fluency with ICH E2F, ICH E2C(R2), and GVP guidelines, including signal management and benefit-risk assessment methodology. Hands-on experience with MedDRA coding, seriousness and causality asse