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Kriya Therapeutics, Inc. is seeking a Vice President of Biometrics to lead all biometrics functions, including biostatistics, programming, and data management.
This executive will shape the statistical strategy for the clinical pipeline and ensure data integrity for regulatory submissions. The role partners with Clinical, Regulatory, Translational, CMC, and Quality to advance programs from early studies through registration, applying advanced trial design and external data approaches where
Department: Clinical
Employment Type: Full Time
Location: Remote
Kriya is a biopharmaceutical company whose mission is to develop life-changing gene therapies for diseases affecting millions of patients around the world.
We leverage our proprietary computational engine, in-house manufacturing infrastructure, and integrated design platform to engineer technologies and therapeutics with the potential to transform the treatment of a broad universe of diseases of high unmet need, with a focus on metabolic disorders, neurology, and ophthalmology.
We are proud to have been named Triangle Business Journal’s Life Sciences 2024 “Best Private Company to Work For,” recognized by Forbes as one of “America’s Best Startup Employers of 2024,” and honored as one of BioSpace’s “2025 Best Places to Work.”
The Vice President, Biometrics leads all biometrics functions at Kriya Therapeutics, including biostatistics, statistical programming, and clinical data management. This leader develops and executes the statistical and data strategy for the clinical pipeline, ensures the integrity and quality of data supporting regulatory submissions, and builds the team and systems needed to move programs from early clinical studies through registration. The role is a member of the clinical development leadership team and a trusted partner to Clinical, Regulatory, Translational, CMC, and Quality.
The VP will apply deep expertise in rare and common disease trial design, novel endpoints, and natural history and external control approaches to a modality where the data package must be both rigorous and efficient.