Overview
Responsibilities and qualifications for CSR authoring and regulatory writing with internal hand-off to GenAI engineering streams.
Responsibilities
- Client discovery, scoping, and requirements (business-side)
- Lead requirements elicitation with client Medical Writing/Regulatory teams for CSR authoring (template standards, TA nuances, target sections, review cadence, acceptance criteria, quality bars).
- Translate business goals (timelines, submission strategy, risk tolerance, review workflows) into clear deliverables and negotiate scope, timelines, and costs; manage change requests and approvals.
- Define “done” for each CSR section (e.g., Safety Evaluation, Efficacy) including scientific tone, numerical consistency, and ICH E3 alignment; maintain a living Requirements & Assumptions log.
- Translation to technical work (internal hand-off)
- Convert business requirements into technical briefs for the GenAI Engineer (priority TLFs, required tables/figures, prompt constraints, style rules, traceability links to sources).
- Specify validation frameworks for GenAI outputs (accuracy, completeness, faithfulness, numerical parity with TLFs) and co‑own evaluation rubrics with engineering.
- Own the backlog for Rapid CSR features during engagements (as Business PO), prioritize bugs/iterations based on medical writing impact and regulatory readiness.
- Run structured review cycles (internal QC → client SME review → stat review) and close comments to final.
Required Skills and Qualifications
- Advanced degree in Life Sciences, Pharmacy, or related field.
- Proven track record (8–12 years) in CSR authoring and regulatory writing.
- Strong understanding of clinical trial processes and regulatory guidelines.
- Working knowledge of GenAI/LLMs and AI/ML SDLC (prompts, evaluation, HIL review, versioning).
- Comfort with clinical data sources (TLFs, SAP, protocol, narratives) and numerical consistency checks.
- Excellent planning, negotiation, and stakeholder management skills.
Soft Skills
- Work closely with cross-functional teams, including clinical data engineers, clinical data modelers, front end developers, QA/CSV specialists, clinical SMEs, project managers, and cloud/infrastructure professionals, to understand project requirements and deliver high-quality solutions.
- Maintain thorough documentation of methodologies, processes, and results of the models. Prepare and present detailed reports on assigned projects to stakeholders, including client and internal leadership illustrating the impact and effectiveness of data-driven strategies.