Departmental Overview

D-Lab equips UC Berkeley scholars with the skills, methods, and emerging data science tools to advance their research through hands-on training and expert guidance.

Based in the Division of Social Sciences and in partnership with the Division of Computing, Data Science, and Society, D-Lab's interdisciplinary reach spans the social sciences, arts and humanities, computing, data science, statistics, information science, business, education, engineering, environmental design, journalism, law, public health, public policy, social welfare, natural resources, chemistry, biological and physical sciences.. D-Lab is a research accelerator that equips scholars with the knowledge, skills, and tools for cutting-edge research. D-Lab is a research incubator that co-constructs expansive communities of practice. D-Lab works with Berkeley faculty, research staff, graduate, and undergraduate students to advance data-intensive research. We support the exploration, development, dissemination, and application of methodologies, toolkits, and resources to engage with next-generation data sources through innovative analytics. We think of data as a capacious category, constantly changing as the research frontier moves. D-Lab's signature focus is research design: intelligent, rigorous, and tuned to the transformative opportunities opened up by a data- and computationally rich world.

D-Lab provides cross-disciplinary resources for in-depth consulting and advising, access to staff and peer-to-peer consulting support, and training and provisioning for software and other infrastructure needs. We offer a collaborative venue for intellectual and methodological exchange. By networking with other Berkeley centers and facilities, as well as with our departments and schools, we offer our services to researchers across disciplines and underwrite the breadth of excellence in Berkeley's undergraduate and graduate programs and faculty research.

D-Lab's user base is strongly interdisciplinary and campus-wide, including the professional schools as well as disciplinary departments. It serves thousands of researchers annually through public and private workshops, consulting, events, working groups, data services, and other academic programs, such as the year-long Computational Social Sciences course and the Digital Humanities Summer Minor and Certificate Program. D-Lab has a strong culture of responsiveness to users and empowers professional and graduate staff. It is an internally differentiated organization with several teams while maintaining a relatively flat organizational structure. We are physically located in the Social Sciences Building and the Computing, Data Science, and Society Building, called the Gateway.

Position Summary

The Data Services Manager primarily develops and updates data science curricula, organizes and supports fellowship cohorts, and coordinates special projects that advance D-Lab's research and instructional mission. Working collaboratively with staff, instructors, fellows, and researchers, the manager translates emerging methods and tools into accessible educational programming. The role also provides technical expertise to maintain and improve the data systems that support these activities, ensuring data security, integrity, and accessibility, as well as reliable workflows. This position uses advanced professional data science and data retrieval skills, knowledge, and concepts to resolve highly complex issues. The Data Services Manager serves in key liaison/managerial roles, including serving as the Berkeley Federal Statistical Research Data Center (FSRDC) liaison and manager, a partnership with the US Census Bureau. This position also serves as a liaison to the Census State Data Center (SOC) Network.

Application Review Date

The First Review Date for this job is October 7, 2026. For full consideration, please apply by the first review date.

Responsibilities

Advanced Research Training & Consulting

• Training and curriculum: Designs, develops, teaches, and continuously improves workshops, short courses, customized trainings, tutorials, notebooks, templates, and other reusable learning materials for researchers at different levels of technical experience.
• Advanced AI for research: Provides instruction and consultation on large language models, prompt and context design, model and tool evaluation, retrieval-augmented generation, embeddings, structured outputs, multimodal methods, local and hosted models, and responsible AI practices.
• Agents and APIs: Designs, tests, and teaches API-based and agentic research workflows, including tool use, orchestration, memory and state, human-in-the-loop review, monitoring, error handling, cost management, and reproducible implementation.
• Research consulting: Evaluates research questions, data, constraints, and researcher capacity; recommends appropriate methods; develops analysis plans; troubleshoots technical problems; and supports projects from design and data acquisition through analysis, validation, visualization, and dissemination.
• Large-scale data matching: Leads the design and implementation of record linkage, entity resolution, deduplication, fuzzy and probabilistic matching, geospatial and temporal matching, crosswalk development, and validation across large and heterogeneous datasets.
• Reproducible systems: Develops robust workflows in Python, R, SQL, version control, cloud, or high-performance computing environments, and related tools; creates documentation, tests, quality-assurance procedures, and reusable code.
• Responsible research: Addresses data privacy, security, intellectual property, bias, transparency, accessibility, research ethics, and appropriate human oversight when using AI and sensitive or restricted data.
• Presentations and outreach: Deliver technical workshops, consultations, demonstrations, and presentations for campus and external audiences, and communicate complex methods clearly to technical and non-technical researchers.

Program Development, Mentoring & Community Building

• Develops new interdisciplinary training, consulting, fellowship, working-group, and research-support programs in response to emerging campus needs and advances in AI and computational research.
• Establishes program goals, curricula, service models, timelines, documentation, assessment plans, and sustainable operating practices; analyzes participation, learning, consultation, and impact data to improve programs.
• Mentors and coaches, instructors, consultants, graduate and undergraduate fellows, project staff, and researchers. Reviews teaching and consulting materials, observes practice, provides feedback, and supports professional and technical development.
• Builds communities of practice that connect researchers across disciplines and levels of expertise; facilitates peer learning, collaborative problem solving, and the sharing of reusable methods and resources.
• Develops partnerships with departments, centers, libraries, government agencies, and external organizations; scopes shared programs, prepares proposals and agreements, and identifies funding and cost-recovery opportunities.
• Represents D-Lab in orientations, outreach activities, demonstrations, and partner meetings and communicates program value, research applications, and outcomes to diverse audiences.

Research Data Systems, AI Infrastructure & Standards

• Develops and maintains secure, scalable research infrastructure for data acquisition, storage, transformation, matching, analysis, and AI-enabled workflows; coordinates with campus technology units, collaborators, and vendors.
• Establishes standards for data governance, documentation, metadata, reproducibility, model and pipeline evaluation, privacy, security, and the responsible use of AI and sensitive data.

Senior Leadership, Institutional Partnerships & Restricted-Data Services

• Participates in D-Lab senior management, strategic planning, resource allocation, grant and contract development, program assessment, and the evaluation of software, computing, and data investments.
• Supports the Berkeley Federal Statistical Research Data Center by evaluating research needs and proposals, advising on restricted data and linkage feasibility, facilitating access and data-use agreements, and coordinating with the Census Bureau and institutional partners.
• Develops institutional partnerships and funding strategies that broaden access to research data, computational methods, training, and consulting services.

Required Qualifications

• Advanced knowledge of computational social science, research design, and multiple forms of research data, including administrative, survey, geospatial, text, social media, and instrument-generated data; demonstrated expertise working with complex and large-scale datasets.
• Demonstrated experience designing, teaching, and evaluating research training, workshops, curricula, or customized instruction for learners with varied disciplinary and technical backgrounds.
• Demonstrated advanced consulting skills, including the ability to translate substantive research questions into feasible methodological and computational plans and to guide projects through implementation and validation.
• Advanced knowledge of AI tools and methods for research, including large language models, prompt and context design, embeddings, retrieval-augmented generation, model evaluation, AI agents, tool use, workflow orchestration, and commercial or open-source APIs.
• Demonstrated knowledge of responsible AI, privacy, data security, intellectual property, accessibility, algorithmic bias, transparency, disclosure limitation, and legal or ethical requirements governing sensitive and restricted data.
• Advanced knowledge of data engineering and management systems, including Python and/or R, SQL, version control, APIs, cloud or high-performance computing, reproducible pipelines, and large-scale record linkage, entity resolution, deduplication, and probabilistic or fuzzy matching.
• Advanced professional knowledge enabling leadership of complex program development, coordination, assessment, partnership, and specialized research-support activities.
• Demonstrated ability to mentor, coach, and develop instructors, consultants, fellows, staff, students, and researchers from diverse backgrounds.
• Demonstrated ability to communicate complex technical information to technical and non-technical audiences through consulting, documentation, public speaking, demonstrations, and instruction.
• Self-motivated and able to work independently and collaboratively. Strong organizational, project-management, and relationship-management skills.
• Demonstrated advanced problem-solving skills, sound judgment, intellectual curiosity, and the ability to learn emerging technologies, manage ambiguity, and meet deadlines.
• Advanced analytical and systems-design skills, including the ability to abstract research requirements, understand information flows, select appropriate architectures, and develop scalable, maintainable, and secure workflows.
• Critical thinking, careful documentation, quality assurance, fact verification, and attention to detail; ability to evaluate the limitations, risks, costs, and research validity of AI-assisted methods.
• PhD in a related area and/or equivalent experience/training.

Salary & Benefits

For information on the comprehensive benefits package offered by the University, please visit the University of California's Compensation & Benefits website.

Under California law, the University of California, Berkeley is required to provide a reasonable estimate of the compensation range for this role and should not offer a salary outside of the range posted in this job announcement. This range takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to experience, skills, knowledge, abilities, education, licensure and certifications, analysis of internal equity, and other business and organizational needs. It is not typical for an individual to be offered a salary at or near the top of the range for a position. Salary offers are determined based on final candidate qualifications and experience.

The budgeted annual range that the University reasonably expects to pay for this position is $115,800 - $160,000.

• This is an exempt, monthly-paid position.
• This is a full-time (40 hours/week) career position eligible for UC benefits.

How to Apply

To apply, please submit your resume and cover letter.

Other Information

• This is not a visa opportunity. This position does not include sponsorship of a new consular H-1B visa petition that would require payment of the $100,000 supplemental fee.
• This position is governed by the terms and conditions of the Technical Unit (TX) agreement between the University of California and the University Professional and Technical Employees (UPTE). The current bargaining agreement manual can be found at: http://ucnet.universityofcalifornia.edu/labor/bargaining-units/tx/index.html