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Salary: USD 130,000 - 200,000 / annual
Brooklyn Health is hiring a Clinical Scientist to lead data quality and integrity oversight for CNS (central nervous system) clinical trials. The Willis platform modernizes the technology stack for CNS clinical trials, improving endpoint quality and reducing placebo response in precision neuroscience research.
In this role, you will oversee the quality, reliability, and integrity of study data by leading rater onboarding and scale training, conducting blinded data surveillance, and overseeing targeted site remediation to safeguard trial endpoints. You'll interface with sponsors and CROs to communicate insights around study data quality and participate in eligibility review meetings, contributing clinical data quality perspectives to eligibility decisions.
Key responsibilities include: providing oversight and expertise to ensure clinical outcome assessment data quality in CNS trials; leading rater training and onboarding, including developing training materials and overseeing rater certification; conducting reviews of study data and making recommendations for site and rater feedback, interventions, and remediation; overseeing targeted site interventions and rater remediation; and collaborating with the Science team to develop and refine study data monitoring methods.
You'll need 5+ years of experience as a Clinical Scientist, Clinical Rater, Rater Trainer, or equivalent position in CNS clinical trials (psychiatry, neurology). An advanced degree in a health sciences field (psychology, psychiatry, nursing, pharmacology) is required. Deep practical familiarity with standard CNS assessments (MADRS, HAM-D, PANSS, HAM-A, CAPS-5, MINI, etc.) is essential, along with meticulous attention to detail and a strong background in clinical data evaluation, quality control frameworks, or trial QA workflows. You should demonstrate the ability to interpret rater performance data, guide clinical decision-making, and manage site-facing interventions constructively.
Nice-to-haves include interest/experience evaluating AI-based clinical decision support tools, proficiency with data visualization tools for identifying data trends, and a record of contributing to empirical findings related to clinical outcome assessments or trial data integrity.
