Data Scientist's

Proclinical is seeking a Data Scientist to support a multi-site research program focused on collecting neural and behavioral data from clinical settings. This role will serve as the principal technical authority on data quality, ensuring incoming data meets rigorous standards for downstream research and AI modeling., The successful candidate will play a pivotal role in developing scalable quality control methods and infrastructure as the program expands. This position is ideal for someone with expertise in computational neuroscience and a passion for working with real-world clinical data., * Evaluate incoming data from partner sites using defined technical criteria to ensure quality standards for research and modeling.

• Develop and implement formal quality metrics for neural and behavioral data, including electrophysiological recordings and behavioral task data.

• Design and apply model-based validation techniques to confirm data suitability for scientific use.

• Utilize machine learning for anomaly detection and streamline quality control processes as data volume increases.

• Provide clear, objective, and reproducible rationale for data quality determinations.

• Monitor and report on quality control outcomes across sites, identifying patterns, training needs, and areas for improvement.

• Collaborate with site personnel and stakeholders to troubleshoot and resolve data quality issues.

• Refine quality control standards and methodologies as the program evolves.

Are you passionate about laboratory operations and equipment management, with a keen eye for documentation, compliance, and process improvement?, * Strong background in computational neuroscience or related field.

• Proficiency in handling and analyzing messy, real-world clinical data.

• Experience developing and deploying quality control metrics for complex datasets.

• Familiarity with machine learning techniques for anomaly detection and process optimization.

• Ability to design model-based validation methods for scientific data.

• Excellent communication skills to provide clear and reproducible data assessments.

• Proven ability to collaborate with diverse teams, including site personnel and research stakeholders.

• Adaptability to refine methodologies and scale infrastructure as the program grows.