OverviewAt PNNL, our core capabilities are divided among major departments that we refer to as Directorates within the Lab, focused on a specific area of scientific research or other function, with its own leadership team and dedicated budget.
Our Science & Technology directorates include National Security, Earth and Biological Sciences, Physical and Computational Sciences, and Energy and Environment. In addition, we have anEnvironmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus.
The Earth and Biological Sciences Directorate (EBSD) leads critical research in four areas: Atmospheric, Climate & Earth Sciences, Biological Sciences, Environmental Molecular Sciences, and Global Change. Our vision is to develop a predictive understanding of biological and Earth systems in transition. We aim to understand energy and material flows within the integrated Earth system; to understand, predict, and control the response of biosystems to environmental and/or genomic changes; and to Model the Earth system from the subsurface to the atmosphere.
The Environmental Molecular Sciences Division is comprised of 18 interdisciplinary research teams focused on deciphering molecular-level interactions driving biological and environmental processes across temporal and spatial scales. Through computational analysis and modeling, these findings contribute to predictive understanding of how systems respond to environmental perturbations thus enabling solutions to the nation’s energy, environmental, and human health challenges. The division also manages the Environmental Molecular Sciences Laboratory, a Department of Energy, Office of Science user facility housed on the PNNL campus that accelerates the research of scientists around the world by providing access to world-class expertise, instrumentation, and computational resources.
The Environmental Molecular Sciences Laboratory (EMSL) is a Department of Energy, Office of Science, User Facility sponsored by the Biological and Environmental Research (BER) program. At EMSL, our researchers advance BER’s mission to achieve a predictive understanding of complex biological, Earth, and environmental systems, collaborating on projects with researchers from academia, other government laboratories, and industry. Scientists around the world partner with us to use our world-class laboratory space, expertise, and equipment, building a research community empowered to study the role of molecular processes in controlling the functioning of biological and ecological systems across spatial and temporal scales, and to enable a predictive understanding of the living Earth system.
EMSL is seeking a Chief Data Officer (CDO) to lead EMSL’s computing and scientific data management strategy and operations. The CDO is responsible for continuous development, implementation and operations of EMSL’s overall digital infrastructure vision through leadership and line management of a group of experts, including IT and software engineers, data architects, data managers, computer scientists, and cyber security professionals. The CDO will have accountability for computing operations; hardware and software acquisitions; networking; data architecture; workflow and archiving decisions; software development; and ensuring that EMSL’s data environment is capable of capturing, securing, and delivering AI‑Ready FAIR data at scale. A key accountability for the CDO will be to execute on a computing and data management strategy that reinforces EMSL’s strategic science directions for sponsors, establishing EMSL as a premier thought leader in heterogenous mid-range computing, networking, and distributed data management for advancing Department of Energy Office of Science basic science research. The CDO serves as a key member of the EMSL leadership team working closely and in constant partnership with EMSL Science Area Leads, Chief Operating Officer, and Chief Science Officer.
EMSL is embarking on a transformative expansion of automated laboratory science through strategic partnerships, including a major collaboration with Ginkgo Bioworks, to build a next‑generation automated laboratory generating unprecedented volumes of high‑quality experimental data. This effort is tightly aligned with the Department of Energy’s Genesis mission, requiring sophisticated data engineering workflows, highly scalable AI/ML pipelines, and robust digital infrastructure to rapidly extract scientific insight from automated, high‑throughput systems. The CDO will play a central leadership role in ensuring that EMSL’s data ecosystems, automation workflows, and AI/ML capabilities are architected and operated to enable this mission.
This position comprises predominantly executive level management responsibilities with significant span of control and/or delegated authority and responsibility. The CDO manages a multi-disciplinary organization through staff leaders and subordinate managers, interacting with and negotiating at the senior management and executive levels. Management decisions impact objectives, goals and long-term success of the organization and Laboratory. Responsibilities may involve line, sector or functional lead responsibilities as part of any compensable factor at any level.
As a senior EMSL executive, the CDO will co‑shape long‑term laboratory strategy, integrating digital, data, and AI capabilities with core scientific priorities and national scientific missions. The CDO will serve as EMSL’s primary strategic voice on data, automation, AI/ML, and cyberinfrastructure in interagency and inter-laboratory forums, representing EMSL’s needs and vision to DOE sponsors and collaborative facilities.
This role requires a highly collaborative and participatory leadership style that builds trust, invites diverse perspectives, and empowers managers, technical staff, and scientific partners to contribute to shared decision‑making and continuous improvement.
- Provide participatory, inclusive leadership that actively engages EMSL staff at all levels - inviting input, fostering shared ownership of decisions, and cultivating a psychologically safe environment where cross‑disciplinary collaboration thrives.
- Model transparency, clarity and openness in decision making, ensuring technical teams, scientists, and operational partners are informed, heard, and meaningfully engaged in shaping data and cyberinfrastructure strategies.
- Develop and mentor leaders and managers within the organization, strengthening leadership bench depth and promoting a culture of accountability, empowerment, and continuous learning.
- Ensure EMSL’s data workforce evolves to meet future automation, AI/ML, and high‑throughput scientific needs by fostering continuous skill development, talent acquisition, and strategic workforce planning.
- Lead strategy development, implementation, and continuous improvement of data generation and complex scientific data engineering workflows supporting EMSL’s automated laboratory initiatives, including the Ginkgo Bioworks collaboration and DOE Genesis mission.
- Oversee the design and operation of scalable AI/ML‑ready data architectures that support automated, high‑throughput experimental pipelines, including near‑real‑time data ingestion, validation, transformation, and analytics.
- Partner closely with scientific and automation teams to ensure automated instruments and laboratory robotics seamlessly integrate with EMSL’s digital ecosystem, enabling reliable, high‑volume capture of AI‑Ready FAIR data.
- Champion and implement advanced AI/ML workflows— including predictive modeling, automated analysis, anomaly detection, and generative model integration— to accelerate scientific discovery from large, heterogeneous datasets.
- Drive organizational adoption of modern data engineering, AI, cybersecurity, and automation best practices, ensuring EMSL remains at the forefront of DOE science and technology innovation.
- Establish a long-term digital modernization roadmap, aligning infrastructure investments with future scientific directions, sustainability goals, and emerging national research priorities.
- Lead and oversee requirements gathering and technical planning to ensure user requirements are translated into technical specifications.
- Lead data architects and data engineers to design, code, test, support, and document software applications that track data source, data movement, analysis, storage and long-term archiving.
- Collaborate closely with software, IT, and data engineering teams, as well as domain scientists to ensure the development of robust and reusable data models and application programming interfaces.
- Communicate effectively with EMSL science leaders and data management project team in a timely manner to escalate issues and risks appropriately.
- Support educational programs for EMSL staff and champion data governance, data quality, and data integrity.
- Lead and participate in the procurement process, RFIs/RFPs, and negotiations with third party vendors in crafting manageable solutions.
- Communicate effectively with CDOs and CTOs of other BER facilities (such as JGI, ARM) and other DOE labs to share best practices and work together on big challenges.
- Provide strategic oversight and prioritization of multi-million-dollar annual budgets, ensuring transparent fiscal stewardship, alignment with strategic goals, and effective balancing of operational reliability and innovation investments.
QualificationsMinimum Qualifications:
- BS/BA and 10 years of relevant experience -OR-
- MS/MA or higher and 8 years of relevant experience
Preferred Qualifications:
- Experience with scientific data architecture, large-scale data modeling, networking and database design, and business requirements gathering analysis, ideally including technical leadership in a user facility organization interfacing with scientific users.
- Previous management experience of a team of 25+ people, including experience leading other managers.
- Demonstrated experience building or managing large‑scale automated laboratory data ecosystems, including high‑throughput experiment data capture, workflow orchestration, and automated data quality assurance.
- Proven track record architecting and delivering AI/ML pipelines for scientific or industrial data at scale, including applications in automation‑driven environments.
- Executive‑level experience leading multi‑disciplinary technical organizations, including oversight of managers, senior technical staff, and cross‑functional teams.
- Demonstrated experience in large scale enterprise and data warehouse initiatives involving multiple departments and organizations, and collaboration with external partners to execute and evolve data strategy.
- Strong communications skills including advocating strategies and processes around data governance and modeling across departments and senior leaders.
- Deep understanding of data governance principles and FAIR data principles, ideally with experience working in an environment where data are privately embargoed prior to public release.
- Knowledge of systems development, including system development life cycle, project management approaches and requirements, design and testing techniques.
- Understanding of predictive modeling, data mining, visualization, machine learning and artificial intelligence, text analysis, and natural language processing.
- Knowledge of data engineering, data cleansing, data analysis, data anomalies detection, and database administration.
- Ability to create complex process flow diagrams or flowcharts that demonstrate business or system process and data flows, solicit feedback and gain stakeholder support through productive iteration.
- Strong problem-solving and analytical skills, creativity and the ability to work with abstract concepts to create innovative and appropriate data architectural proposals and work to ensure their adoption.
- Senior-level experience delivering AI-powered software products and leading teams that use AI as an integral part of the development process, including AI-assisted coding, testing, and architecture design.
- Knowledge of high-performance computing (HPC) systems and hardware.
- Knowledge of cloud computing.
- Knowledge of common data standards, databases, and software tools/frameworks used in biology and chemistry research.
- Familiarity with emerging AI agent technologies and standards (e.g. Model Context Protocol).
- Demonstrated executive-level experience leading through openness, transparency, and participatory leadership, actively involving staff in decision processes, creating shared vision, and enabling teams to influence strategy, operations, and organizational culture.
- Experience ensuring compliance with federal cybersecurity, privacy, and data protection requirements, ideally within a DOE or federal research environment.
- Demonstrated ability to lead organizational change, modernize legacy systems, and drive adoption of new technologies and workflows.
Hazardous Working Conditions/EnvironmentNot Applicable
Testing Designated PositionThis is not a Testing Designated Position (TDP).
About PNNLPacific Northwest National Laboratory (PNNL) is a world-class research institution powered by a highly educated, diverse workforce committed to the values of Integrity, Creativity, Collaboration, Impact, and Courage. Every year, scores of dynamic, driven people come to PNNL to work with renowned researchers on meaningful science, innovations and outcomes for the U.S. Department of Energy and other sponsors; here is your chance to be one of them!
At PNNL, you will find an exciting research environment and excellent benefits including health insurance, and flexible work schedules. PNNL is located in eastern Washington State—the dry side of Washington known for its stellar outdoor recreation and affordable cost of living. The Lab’s campus is only a 45-minute flight (or ~3 hour drive) from Seattle or Portland, and is serviced by the convenient PSC airport, connected to 8 major hubs.
Commitment to Excellence and Equal Employment OpportunityOur laboratory is committed to fostering a work environment where all individuals are treated with fairness and respect while solving critical challenges in fundamental sciences, national security, and energy resiliency. We are an Equal Employment Opportunity employer.
Pacific Northwest National Laboratory (PNNL) is an Equal Opportunity Employer. PNNL considers all applicants for employment without regard to race, religion, color, sex, national origin, age, disability, genetic information (including family medical history), protected veteran status, and any other status or characteristic protected by federal, state, and/or local laws.
We are committed to providing reasonable accommodations for individuals with disabilities and disabled veterans in our job application procedures and in employment. If you need assistance or an accommodation due to a disability, contact us at careers@pnnl.gov.
Drug Free WorkplacePNNL is committed to a drug-free workplace supported by Workplace Substance Abuse Program (WSAP) and complies with federal laws prohibiting the possession and use of illegal drugs.
If you are offered employment at PNNL, you must pass a drug test prior to commencing employment. PNNL complies with federal law regarding illegal drug use. Under federal law, marijuana remains an illegal drug. If you test positive for any illegal controlled substance, including marijuana, your offer of employment will be withdrawn.
Security, Credentialing, and Eligibility RequirementsAs a national laboratory, PNNL is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require new employees to obtain and maintain a HSPD-12 Personal Identify Verification (PIV) Credential. To obtain this credential, new employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
For foreign national candidates:
If you have not resided in the U.S. for three consecutive years, you are not eligible for the PIV credential and instead will need to obtain a favorable Local Site Specific Only (LSSO) Federal risk determination to maintain employment. Once you meet the three-year residency requirement thereafter, you will be required to obtain a PIV credential to maintain employment. The tier of federal background investigation required to obtain the PIV credential will be determined by job duties at the time you become eligible for the PIV credential.
Mandatory RequirementsPlease be aware that the Department of Energy (DOE) prohibits DOE employees and contractors from having any affiliation with the foreign government of a country DOE has identified as a “country of risk” without explicit approval by DOE and Battelle. If you are offered a position at PNNL and currently have any affiliation with the government of one of these countries, you will be required to disclose this information and recuse yourself of that affiliation or receive approval from DOE and Battelle prior to your first day of employment.
Rockstar RewardsEmployees and their families are offered medical insurance, dental insurance, vision insurance, robust telehealth care options, several mental health benefits, free wellness coaching, health savings account, flexible spending accounts, basic life insurance, disability insurance*, employee assistance program, business travel insurance, tuition assistance, relocation, backup childcare, legal benefits, supplemental parental bonding leave, surrogacy and adoption assistance, and fertility support. Employees are automatically enrolled in our company-funded pension plan* and may enroll in our 401 (k) savings plan with company match*. Employees may accrue up to 120 vacation hours per year and may receive ten paid holidays per year.
* Research Associates excluded.
**All benefits are dependent upon eligibility.
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Notice to ApplicantsPNNL lists the full pay range for the position in the job posting. Starting pay is calculated from the minimum of the pay range and actual placement in the range is determined based on an individual’s relevant job-related skills, qualifications, and experience. This approach is applicable to all positions, with the exception of positions governed by collective bargaining agreements and certain limited-term positions which have specific pay rules.
As part of our commitment to fair compensation practices, we do not ask for or consider current or past salaries in making compensation offers at hire. Instead, our compensation offers are determined by the specific requirements of the position, prevailing market trends, applicable collective bargaining agreements, pay equity for the position type, and individual qualifications and skills relevant to the performance of the position.
Minimum SalaryUSD $177,900.00/Yr.
Maximum SalaryUSD $266,900.00/Yr.
