Associate Director, In Vivo Digital Portfolio & Data Stewardship

Role Summary

Associate Director of In Vivo Digital Portfolio & Data Stewardship to drive digital enablement and data quality across the preclinical in vivo research organization. This role bridges science, operations, and technology to ensure seamless integration of study workflows, regulatory compliance, and data interoperability across platforms. The successful candidate will translate scientific and business needs into digital solutions that enhance study execution, data integrity, and decision-making. Location: Boston, MA.

Responsibilities

• Digital Strategy & Roadmap: Partner with Research, digital (RDDT) teams to define and implement the digital vision for in vivo workflows.
• Preclinical Study Workflow Support: Guide the design and optimization of study processes, spanning protocol setup, randomization, dosing, in life data collection, observations, sample collection, necropsy, and reporting.
• Data Stewardship & Interoperability: Ensure robust data standards and harmonization (animal IDs, sample IDs, study IDs) across systems such as Benchling In Vivo, Tetrascience, Pristima, and Studylog, enabling interoperability with sample registration, study identification, and electronic lab notebooks (eLN).
• Integration of CRO Datasets: Lead the ingestion, mapping, and standardization of external CRO-generated in vivo datasets into internal workflows (e.g., Benchling In Vivo), ensuring data consistency, regulatory alignment, and reusability for downstream analytics.
• Vivarium Operations & Compliance: Support digital workflows in animal care, cage/room management, and compliance with IACUC/GLP standards.
• Cross-Functional Collaboration: Serve as a trusted partner across Research Units, Digital R&D, Quality, and Operations to ensure business needs are aligned with digital delivery.
• Audit & Data Integrity: Champion ALCOA+ principles, ensuring audit-readiness of all in vivo data and compliance with electronic record-keeping regulations.
• Metrics & Adoption: Define, monitor, and report on study-level KPIs (e.g., cycle times, missed observations, protocol deviations, adoption rates).

• Digitization & Data Foundations: Drive alignment of in vivo study data with FAIR principles (Findable, Accessible, Interoperable, Reusable) to ensure high-value reusability of preclinical endpoints.
• Ontologies & Controlled Vocabularies: Establish and maintain ontologies and controlled vocabularies to harmonize study designs, procedures, and endpoints across systems and therapeutic areas.
• GUPRIs (Globally Unique Persistent Identifiers): Implement for animals, samples, procedures, and endpoints to enable consistency and traceability across workflows.
• Reuse of In Vivo Endpoints: Build the digital foundation that allows reuse of in vivo endpoints for advanced analytics, machine learning, and AI-driven insights.
• Partnership with Data Science: Collaborate to ensure in vivo data structures support predictive modeling, translational alignment, and decision-making.

Qualifications

• Required: Deep understanding of in vivo preclinical study workflows and the ability to engage with both scientific and technical stakeholders.
• Required: Knowledge of vivarium operations, including cage/room management, animal identification, and regulatory compliance (IACUC, GLP).
• Required: Proven expertise in data modeling and interoperability for animal and procedure-level data across digital platforms.
• Required: Strong communication skills with the ability to translate complex workflows into digital requirements.
• Required: Experience with workflow-driven platforms such as Benchling In Vivo, Benchling eLN, Pristima, and Studylog.
• Required: Demonstrated leadership in driving cross-functional alignment and influencing adoption of new tools and standards.
• Required: 5–10 years’ experience in the Pharma and/or Biotech industry, with a singular focus on preclinical in vivo research, and secondary focus on digital enablement and data stewardship of in vivo research.

• Preferred: Experience in therapeutic area–specific in vivo workflows (e.g., DDU).
• Preferred: Background in PKPD modeling and end-to-end in vivo/ex vivo workflows.
• Preferred: Exposure to safety/toxicology and pathology data workflows to support Safety (NCSP).
• Preferred: Experience with domain-specific testing and QA in digital tools for in vivo research.
• Preferred: Familiarity with defining test scenarios for dosing, tumor measurements, body weights, and clinical observations.
• Preferred: Proficiency in Japanese is a strong plus.
• Preferred: Skilled in facilitating dialogue between stakeholders with differing priorities, ensuring mutual understanding and alignment.
• Preferred: Ability to translate complex technical concepts into business-relevant language and vice versa.

Education

• Bachelor’s or Master’s degree in Life Sciences, Data Science, or related field