Sage Bionetworks - Associate Director, Computational Biology
Requirements
• Education • Education • Master’s or PhD in a relevant scientific, data, or informatics discipline (e.g., biology, bioinformatics, data science, library/information science, or a related field), or equivalent depth of experience in lieu of an advanced degree. • Master’s or PhD • Advanced technical and domain expertise in data stewardship, applied analysis, and community-building, rather than an independent publication-focused research program. • 8+ years of progressive experience in scientific research, biomedical data management, data governance, research data curation, or a closely related field, including leadership of complex, multi-stakeholder data or collaborative science initiatives. • 8+ years • Experience working in multi-institutional collaborations and consortia. • 3+ years of experience directly managing, mentoring, and/or developing data managers, computational biologists, bioinformaticians, or community engagement professionals. • 3+ years • Track record of securing research funding as a principal investigator, co-investigator, or named key personnel, including at least one competitive NIH or comparable award. • Experience across the proposal lifecycle, including opportunity identification, partner collaboration, budget and effort planning, and post-award reporting. • Demonstrated experience applying open science and FAIR data principles and supporting responsible data sharing for human subjects data. • Experience with GA4GH standards or comparable genomic/clinical data-sharing frameworks. • Experience building or activating a research community around a shared data resource or platform. • Experience collaborating with and coordinating external scientists or consortium partners. • Experience managing funder relationships and communicating scientific and data value to program officers and sponsors. • Ability to operate strategically while remaining close enough to data operations and community activity to identify and address emerging issues. • Ability to influence decisions and create alignment across teams and leaders without relying solely on formal authority. • Strong judgment and ability to navigate ambiguity, competing priorities, and evolving organizational needs. • Experience with biomedical data standards and common data models, such as OMOP, FHIR, GA4GH Phenopackets, or Data Use Ontology. • Familiarity with data-sharing platforms and portals such as Synapse, dbGaP, or EGA and controlled-access data governance. • Experience with NIH Genomic Data Sharing Policy, Data Management and Sharing Policy, or comparable funder requirements. • Hands-on experience analyzing imaging and spatial biology data, including spatial transcriptomics, multiplexed tissue imaging, or digital pathology. • Experience with AI-assisted or agentic workflows for data curation, validation, or community support. • Experience with NIH-funded or comparable large-scale research consortia and public-private partnerships. • Experience developing scientific, biomedical data management, or community-engagement career frameworks, competency models, or mentoring programs. • The following cognitive and physical activities outline the essential functions required for successful job performance. Reasonable accommodations may be provided to enable individuals with disabilities to fulfill these functions. • Physical Demands • Physical Demands • Extended periods of sitting at a desk and using a computer. • Repeated wrist, hand, and finger movements. • Requires clear vision for tasks like data analysis, transcribing, computer use, and reading. • Occasionally lifting or moving objects weighing up to 10 pounds. • Cognitive Demands • Cognitive Demands • Able to work effectively under deadlines. • Strong problem-solving and analytical skills. • Attention to detail and accuracy. • Flexibility to adapt to changing environments, priorities and multitask. • Additional Functions • Travel two times per year for on-site events in Seattle, WA. • Effective verbal and written communication skills. • Works well in a team and maintains professionalism. • Follows company policies, procedures, and relevant laws and regulations. • Note: This list is not exhaustive and may be subject to modification as job duties evolve.
Responsibilities
• Lead Biomedical Data Science & Stewardship: • Applied Data Science: Apply statistical, bioinformatic, and computational biology methods—including exploratory analysis, benchmarking, and tooling—to Sage’s large-scale, multi-omic data to improve usability, discoverability, and scientific value. • Applied Data Science: • Data Management & Curation: Oversee the curation, organization, annotation, and lifecycle management of biomedical datasets in alignment with FAIR principles. • Data Management & Curation: • Data Governance: Partner with Sage’s Privacy and Compliance Office to inform data governance frameworks and access-control models and ensure responsible, ethical, and compliant data sharing. • Data Governance: • Standards & Interoperability: Champion FAIR principles and relevant GA4GH standards, including data-use ontologies, federated data access, and genomic data-sharing frameworks. • Standards & Interoperability: • Data Quality & Harmonization: Lead harmonization of complex, multi-source biomedical datasets to enable cross-study and cross-consortium analysis and reuse. • Data Quality & Harmonization: • Risk & Compliance: Identify and manage data governance, privacy, and compliance risks across the data portfolio. • Risk & Compliance: • Build Community & Team Capability: • Scientific Community Management: Build and sustain a community of internal and external researchers through engagement programs, community meetings, documentation, and direct outreach. • Scientific Community Management: • External Collaboration: Collaborate with and coordinate the research of external scientists and consortium partners using Sage’s data, serving as a scientific liaison. • External Collaboration: • People Management: Hire, manage, and develop a multidisciplinary team of biomedical data managers, community engagement staff, and program managers. • People Management: • Talent Development & Mentorship: Mentor team members across data stewardship, computational biology, program management, and community engagement, supporting growth toward greater independence and technical leadership. • Talent Development & Mentorship: • AI & Data Operations: Ensure effective tools, systems, and practices for data operations, including responsible use of AI-assisted and agentic workflows for curation, validation, and community support. • AI & Data Operations: • Funding & Sustainability: Lead grant proposals and funding strategies that support data infrastructure, program management, governance, and community programs. • Funding & Sustainability: • Continuous Improvement: Establish clear growth paths and continuously improve how Sage manages, governs, and builds community around its data in partnership with People Operations. • Continuous Improvement:
Benefits
• Sage Bionetworks implements equitable workplace strategies to ensure fair pay. Actual compensation is determined by market data, specific experience, and internal parity. • Job Level: Associate Director • Associate Director • Annual Salary Range: $140,000 - $180,000 • $140,000 - $180,000 • Note: New hires typically receive an offer between the minimum and the midpoint of the range to allow for future growth within the role. Higher offers may be considered for exceptional experience or specific market conditions. • Comprehensive Benefits: We offer a package competitive with both commercial biotech and nonprofit sectors: • Health & Wellness: Comprehensive medical, dental, vision, life, AD&D, and long-term disability. • Future Security: Robust retirement plan and flexible spending accounts (FSA). • Work-Life Harmony: Paid time off and flexible work arrangements. • Learn more at: Benefits – Sage Bionetworks • Equal Opportunity & Inclusion
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