Director, Research Administration Data Strategy and Insights - Stanford - Stanford

Description

Director Of Research Administration Data Strategy & Insights

The Director of Research Administration Data Strategy & Insights provides strategic leadership for the data, analytics, and governance infrastructure that underpins the Stanford School of Medicine's Research Operations. As a key member of the Research Operations leadership team reporting to the Assistant Dean, Research Operations, the Director leads an enterprise-wide strategy that unifies systems, standardizes metrics, and ensures real-time, data-driven visibility across the full research administration lifecycleincluding pre-award, clinical trials, research contracting and agreements, compliance, and workforce development.

This role sits at the intersection of research administration and advanced data strategy, blending operational insight with technological expertise to build the modern analytics infrastructure that Stanford Medicine requires. The Director leads a team developing institutional dashboards, KPIs, reporting frameworks, and predictive analytics that reflect the scientific complexity of the School of Medicine and the evolving needs of a data-driven research enterprise. By integrating previously siloed data sources and implementing scalable, transparent reporting environments, the Director enables leadership to monitor performance, anticipate emerging needs, and confidently steer institutional strategy.

Serving as a cross-functional partner, the Director collaborates closely with faculty, department administrators, and leaders across Research Operations, the School of Medicine, and institutional stakeholders. The ideal candidate will drive innovation in research administration by evaluating emerging technologies, advancing data governance, and establishing a unified source of truth that enhances transparency, audit readiness, and operational excellence.

This is a pivotal leadership position for a forward-thinking expert who brings together research administration acumen and technological innovation to build a modern, data-powered ecosystem that enables Stanford Medicine to accelerate discovery and advance its mission.

Duties Include*:

• Lead cross-functional research operations data governance by chairing institutional leadership and Data Strategy Council forums to align definitions, standards, and strategic priorities across Grants, Clinical Trials, Agreements & Compliance, and Training & Outreach.
• Design and implement a formal governance and intake framework that prioritizes analytics and reporting requests, aligns demand with capacity, and ensures timely delivery of high-impact metrics for executive decision-making.
• Define, validate, and maintain enterprise KPIs through cross-functional collaboration, ensuring consistent, institutionally aligned metrics that promote transparency and accountability.
• Develop and deliver operational dashboards and predictive analytics to inform grant proposal performance, clinical trial activation and enrollment, agreement turnaround times, compliance monitoring, training outcomes, and resource planning.
• Enable enterprise system interoperability and data integration across platforms including OnCore, SeRA, REDCap, EPIC, IRB systems, and OPACS by establishing data entry, metadata, and technical integration standards.
• Provide role-specific, self-service analytics tools for departments and faculty that surface actionable insights, reduce reliance on ad hoc reporting, and support decentralized, data-informed decision-making.
• Ensure audit readiness and regulatory compliance by overseeing documentation practices, data lineage, and metadata capture, and coordinating cross-functionally to meet NIH, FDA, sponsor, and internal audit requirements.
• Build and sustain institutional data stewardship and literacy by training embedded domain data stewards, leading change management initiatives, and establishing documentation and knowledge-transfer standards to ensure data quality and operational continuity.

Desired Qualifications:

• Master's or PhD degree in a relevant discipline.
• Professional certification in data management, analytics, or project/program management.
• 12+ years of progressively responsible experience in data science, research administration analytics or related fields.
• Demonstrated success leading organizational transformation or research data system redesign within an academic or research institution.

Education & Experience (Required):

Master's or PhD degree in computer science, data science, statistics, or a related field and 10 years of relevant experience, or combination of education and relevant experience. At least 5 years of leadership experience with complex research projects and supervision of teams.

Knowledge, Skills and Abilities (Required):

• Demonstrated success in leading teams to apply data science, machine learning, and other advanced computing techniques to solve complex research problems.
• Expertise in data science, machine learning methodologies, and tools, with a proven ability to apply these in a research context.
• Strong programming skills, with proficiency in Python and experience with other research software (e.g., R, Stata, Matlab, SAS, Julia, JavaScript).
• Demonstrated experience preferred with data processing at scale, including a deep understanding of the appropriate tools and methodologies for various scenarios.
• Familiarity with advanced text and image processing techniques, and experience developing and deploying full-stack applications and API integrations in a research setting.
• Exceptional problem-solving skills, creativity in developing customized solutions, and the ability to foresee and navigate future technological challenges.
• Strong leadership and interpersonal skills, with the ability to inspire, influence and motivate and mentor a diverse team, foster collaboration, effective working relationships and communicate effectively with a wide range of stakeholders.
• Commitment to continuous learning and staying abreast of the latest technologies and methodologies in research computing.
• Service-oriented leadership style, with an emphasis on supporting and developing team members and facilitating the success of researchers with varying levels of technical expertise.
• Ability to synthesize and articulate technical and scientific methodologies, specifications, and information.
• Demonstrated ability to strategically manage and execute project budgets.
• Exceptional customer relationship and consensus building skills.
• Ability to resolve complex issues quickly and make decisions that meet university objectives in a collaborative culture.

Physical Requirements*:

• Constantly perform desk-based computer tasks.
• Frequently sit, grasp lightly/fine manipulation.
• Occasionally stand/walk, writing by hand.
• Rarely use a telephone, lift/carry/push/pull objects that weigh up to 10 pounds.

Working Conditions:

• May work extended hours, evening, and weekends.
• Travel on campus to schools/units.

Work Standards:

• Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
• Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
• Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide.