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The client is seeking an external expert who brings a decision-maker’s mindset — someone who has personally driven translational pharmacology choices under governance and uncertainty. ### Who we’re looking for - Has owned FIH starting dose, SAD/MAD design, and Phase 2 dose selection for multiple assets. - Participated in governance or review boards, defending dose/exposure rationale in front of senior leadership or regulators. - Demonstrates ability to balance nonclinical → clinical translation: tox, PK, PD, potency, and MoA. - Can articulate the real decision calculus behind dose selection (safety, pharmacology, speed-to-proof). - Capable of turning narrative judgment into explicit decision rules and rubrics for AI training and evaluation. ### Experience level - ~10+ years in major biopharma or biotech (e.g., Lilly, Roche, AbbVie, Amgen, Novartis, GSK, Regeneron, Vertex, Incyte, Gilead) or in specialized translational pharmacology consulting. - Has personally led FIH dose and/or SAD/MAD escalation for ≥2–3 assets. - Proven governance experience: IND sign-off, dose justification memos, exposure–response presentations. - CV or track record includes statements like or - Avoid pure modeling profiles; the ideal expert has decision accountability, not just analytical skill. ### Expectations - Write “golden” FIH dose rationales and escalation strategies for representative programs. - Encode the decision heuristics and trade-offs used by senior translational leaders into structured guidance and rubrics. - Surface unwritten decision rules — when and why experienced teams override model-based recommendations. Inputs given: - Representative drug programs or data packets (GLP tox summaries, PK/PD tables, potency & MoA context). - Target prompts for translational decision-making (e.g., ). Expected outputs: - Golden Decision Memos: exemplar dose justification memos that reflect the level of reasoning and format expected from top-tier translational pharmacologists. - Decision Rubrics: scoring guides capturing acceptable vs. unsafe dose rationales, missed edge cases, or failure modes. - Meta-Layer Commentary: short narrative explaining unspoken heuristics — how senior teams weigh risk tolerance, potency data, or tox uncertainty.