Associate Director, Computational Biology

About Us
Sage Bionetworks uses open science and collaboration to improve human health. We bring together scientific, technical, and operational expertise to advance biomedical research through responsible data sharing, strong governance, and innovative approaches to research and technology.
Our work is complex, interdisciplinary, and mission-driven. We value curiosity, diverse perspectives, experimentation, accountability, and radical collaboration.
The Opportunity
Sage Bionetworks is seeking an Associate Director, Computational Biology to lead and grow a multidisciplinary team focused on applied scientific research, biomedical data stewardship, and community engagement around Sage’s data assets, including widely used resources such as Synapse, the AD Knowledge Portal, and the Cancer Complexity Knowledge Portal.
This is a scientific and people leadership role with an opportunity to shape how Sage curates, governs, shares, and activates its biomedical data. You will establish scientific direction, data management standards, and community-engagement practices in partnership with Sage’s governance and platform teams. Your work will help ensure Sage’s data are Findable, Accessible, Interoperable, and Reusable (FAIR), aligned with GA4GH data-sharing standards, and trusted and actively used by the research community.
You will lead a multidisciplinary team of biomedical data managers, biomedical data engineers, community engagement staff, and program managers. You’ll also serve as a strategic partner to organizational leadership, connect data stewardship and community initiatives to Sage’s broader mission, identify opportunities to expand adoption of Sage’s data assets, and contribute to platform development priorities.
Externally, you will represent Sage with data generators, researchers, funders, consortium partners, and other stakeholders. You will communicate the scientific value of Sage’s managed data, data derivatives, and software platforms while identifying community needs and opportunities for growth.
This role combines scientific leadership, people leadership, and hands-on technical work. You will develop your team, strengthen Sage’s data stewardship and community capabilities, and continue contributing directly through computational biology, statistical, and bioinformatic work. The role is intentionally focused on applied, data- and community-oriented science rather than maintaining an independent, hypothesis-driven research program.
The current scope includes substantial work with spatial and imaging data. You should have the practical technical understanding needed to design effective approaches for complex datasets, including large-scale, multi-omic data, and to evaluate emerging assays, data modalities, and computational methods.
You'll Know You're Succeeding When
Sage’s biomedical data are well curated, governed, documented, and shared in ways that meet FAIR and GA4GH standards.
Researchers actively use, contribute to, and help improve Sage’s data resources.
Data sharing is responsible, ethical, and compliant, with appropriate access and minimal unnecessary friction.
External scientists have well-coordinated and well-supported research experiences with Sage.
Your team has clear expectations, effective practices, and the support needed to deliver high-quality data stewardship and community programs.
Data quality, metadata, and harmonization practices support cross-study and cross-consortium reuse.
You identify opportunities for new projects, collaborations, and funding, including contributing to or leading competitive grant proposals.
You are a trusted scientific and data stewardship partner to internal leadership and the external research community.
Sage is well represented in large-scale Data Coordination Center (DCC) and consortium initiatives, including engagement with program officers, leading scientists, and other stakeholders.
You balance strategic leadership, team development, and hands-on scientific contribution based on program needs.
Note: Please do not upload your resume as your cover letter (required)
Key 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.
Data Management & Curation: Oversee the curation, organization, annotation, and lifecycle management of biomedical datasets in alignment with FAIR principles.
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.
Standards & Interoperability: Champion FAIR principles and relevant GA4GH standards, including data-use ontologies, federated data access, and genomic data-sharing frameworks.
Data Quality & Harmonization: Lead harmonization of complex, multi-source biomedical datasets to enable cross-study and cross-consortium analysis and reuse.
Risk & Compliance: Identify and manage data governance, privacy, and compliance risks across the data portfolio.
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.
External Collaboration: Collaborate with and coordinate the research of external scientists and consortium partners using Sage’s data, serving as a scientific liaison.
People Management: Hire, manage, and develop a multidisciplinary team of biomedical data managers, community engagement staff, and program managers.
Talent Development & Mentorship: Mentor team members across data stewardship, computational biology, program management, and community engagement, supporting growth toward greater independence and technical leadership.
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.
Funding & Sustainability: Lead grant proposals and funding strategies that support data infrastructure, program management, governance, and community programs.
Continuous Improvement: Establish clear growth paths and continuously improve how Sage manages, governs, and builds community around its data in partnership with People Operations.
Qualifications
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.
Advanced technical and domain expertise in data stewardship, applied analysis, and community-building, rather than an independent publication-focused research program.
Experience
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.
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.
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.
Nice to Have
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-assiste

Work arrangement
Yes