AI Product Evaluation Lead – Life Sciences (New...

Dice is the leading career destination for tech experts at every stage of their careers. Our client, Activesoft, Inc., is seeking the following. Apply via Dice today!<br><br><strong>AI Product Evaluation Lead – Life Sciences<br><br></strong><strong>New Jersey, NJ (Onsite Job)<br><br></strong><strong>6 Months Contract<br><br></strong>Evaluate emerging AI/ML tools and platforms for applicability across Life Sciences R&D domains (Biostatistics, Regulatory Affairs, Clinical Quality, Safety, and R&D Operations), with a highly hands on approach to testing, validation, and workflow fit.<br><br>Lead rapid proof of concept (POC) initiatives — including scoping, data requirements, model evaluation, prototype buildout, and end user workflow integration.<br><br>Perform deep hands on assessments of vendor solutions, scrutinizing functionality, model behavior, stability, and real world readiness. Apply a mature, critical lens to identify issues, hidden risks, edge cases, and overstatements in vendor claims.<br><br>Assess vendor solution maturity, including roadmap credibility, architectural soundness, integration feasibility, and alignment with enterprise standards.<br><br>Prepare clear readouts, decision frameworks, and recommendations for senior R&D stakeholders, including go/no go decisions and prioritization options.<br><br>Collaborate with cross functional SMEs (biostats, regulatory, quality, clinical, data management) to translate scientific and operational needs into AI requirements and evaluate feasibility.<br><br>Develop comparison matrices, evaluation frameworks, and scoring criteria for AI tools, incorporating both technical performance and Life Sciences–specific validation requirements (GxP and non GxP).<br><br>Present findings through demos, deep dive sessions, and executive level summaries, distilling complex technical assessments into actionable insights.<br><br>Support documentation, risk assessments, and AI compliance considerations, including explainability, privacy, data controls, auditability, and model governance.