Director, Scientific Data Division

Berkeley, CA

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Lawrence Berkeley National Lab

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Director, Scientific Data Division - 97574

Division:  DD-Data Science


Lawrence Berkeley National Laboratory is seeking an experienced scientific leader with an outstanding record of research accomplishments in data science, computer science, computational science, applied math, or related fields to serve as the Director of the Scientific Data (SciData) Division.


About the Position:

This is an unparalleled opportunity to lead a research division that is internationally recognized for excellence in computer science, data science, and computational research, and to foster an environment that supports high-quality scientific research in foundational and groundbreaking fields and further advances in data-intensive computational science.


The SciData Division Director oversees a staff of 100 employees and affiliates and an annual budget of $30 million. Responsibilities include:

• Providing vision and leadership for the Division;

• Overseeing research, operations, finance, human resources, and environmental health and safety;

• Establishing a culture of excellence and inclusion by recruiting a diverse team of outstanding scientists and staff, enthusiastically supporting and promoting their career development; and

• Advancing Berkeley Lab’s stewardship values of team science, innovation, trust, respect, and service, including building and maintaining a culture that is committed to the ideals of Inclusion, Diversity, Equity, and Accountability.


Reporting to the Associate Laboratory Director for Computing Sciences, the SciData Director serves as a member of the executive team of the Computing Sciences Area, comprising the National Energy Research Scientific Computing Center (NERSC), Scientific Networking, and Applied Mathematics and Computational Research Divisions in addition to the SciData Division. The Director builds collaborative partnerships and programs within the Computing Sciences Area, with other Divisions at Berkeley Lab, and with external research institutions to contribute to large-scale, multidisciplinary initiatives, such as quantum information science and Artificial Intelligence.


About the Scientific Data Division:

The SciData Division transforms data-driven discovery and understanding through the development and application of novel data science methods, technologies, and infrastructures in partnership with science domain experts. Its work in machine learning involves researching, developing and sharing the algorithms, software, tools, and libraries that are fundamental to scientific machine learning. The Division builds tools and models that transform data generated by simulations, experiments, and observations to a form that researchers can manipulate to gain scientific insight. It advances and leverages data management, analytics, and security techniques to solve important problems in scientific cyber infrastructure and energy delivery systems. The Division also leads software engineering, software release management, and software development efforts that promote the visibility, usability, reliability, and sustainability of software products in domains from chemical engineering to high-energy physics.


Just as research and development programs benefit science, domain scientists influence and contribute to the direction and content of SciData’s research. SciData works in partnership with a variety of experts in domains ranging from biology and materials science to fundamental physics and climate science to develop tools, techniques, and technologies to meet the data-analysis challenges posed by present and future experimental, observational, and simulation data. SciData researchers regularly win Best Paper awards, are called upon to give keynote addresses at international conferences, and develop leading-edge software that researchers worldwide use to produce impactful results.


The SciData Division has a diverse funding portfolio, including from the U.S. Department of Energy (DOE) Office of Science. Learn more about the SciData Division here.


Key Responsibilities:

Research Direction:

• Provide scientific and operational leadership for SciData research programs, overseeing a $30-million portfolio and approximately 100 staff, including scientists, postdoctoral fellows, professional staff, and students, as well as several affiliates.

• Develop new initiatives advancing a long-term research vision and strategic plan aligned with national goals, and working collaboratively with Berkeley Lab senior leadership.

• Play a key role in the formulation and direction of Laboratory programs, strategy, and research policies that enhance Berkeley Lab’s preeminence as a National Laboratory. 


Partnership, Communications, and Culture:

• Work closely with Division Directors and Associate Lab Directors across the Laboratory to support existing high visibility collaborations and identify new opportunities to collaborate.

• Develop cooperative programs with colleagues at University of California and other research institutions.

• Establish and communicate the SciData Division’s mission, goals, programs, and accomplishments to Division staff and funding sponsors, Berkeley Lab staff and leadership, and to the broader research community.

• Liaise with DOE and other funding agencies, in partnership with other DOE Laboratories, to champion data science research, influence future research directions, and communicate new ideas; implement DOE policies as they impact the SciData Division.

• Foster a culture of diversity, inclusion, equity, and accountability by: following best practices in recruitment and promotion; engaging staff at all levels through communication, involvement, and recognition; and encouraging diverse committees and panels.


Research Operations:

• Ensure operational effectiveness and compliance, in partnership with the Operations Deputy, across the operations areas, including budgets, funding, workforce planning, human resources management, environmental health and safety, property, space, and facilities management.

• Guide strategies for hiring, retaining, and developing a diverse and productive staff.

• Help assure the efficient, effective, and safe operation of the Laboratory as a member of Berkeley Lab’s scientific and operational management team.




• Ph.D. or equivalent education/experience in computer science, data science, applied math, or a related field, and at least 10 years of professional experience.


Research Expertise: 

• An expert and leader in an area of computer science, data science, computational science, applied math, or other fields related to the SciData Division’s research programs. 

• Strong record of research accomplishments, as evidenced by scholarly publications, patents, development and release of software products, and/or funded research grants.


Research Program Development & Management: 

• Experience and demonstrated competence in the management of scientific projects and collaborative science.

• Strategic leadership ability applicable to running a diverse, team-oriented organization with a multidisciplinary group of scientists and engineers.

• Ability to interact effectively with funding agencies and initiate substantial new research efforts and collaborations.


Communications and Culture:

• Effective interpersonal and communication skills, and the ability to interact at the highest level of management, both internally and externally, in a constructive and collaborative manner and in a way that appropriately represents the Laboratory.

• Commitment to diversity, inclusion, equity, and accountability, including a commitment to mentoring and career development of personnel.


Research Operations:

• Experience in effective oversight of operational functions, creativity in decision making and problem solving, and experience in human resource management.


Application Guidelines:

• For full consideration, please submit your CV and cover letter by February 15, 2023. 

• In the cover letter, highlight your interest and vision for the position as well as relevant professional experience and accomplishments, including personal contributions to diversity, equity, and inclusion.



• This is a full-time career appointment, exempt (monthly paid) from overtime pay.

• This position is expected to pay $325,000 to $365,000 annually; salary for this position will be commensurate with the final candidate’s qualifications and experience, including skills, knowledge, relevant education, certifications, as well as aligned with the internal leadership peer group. Please note the above pay scale fits within the full salary range of $220,380 to $457,392 for the Scientific Division Director job classification. It is not typical for an individual to be offered a salary at or near the top of the full range for a position.

• This position may be subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.

• The Scientific Data Division Director position is a career position that is appointed by and serves at the discretion of the Laboratory Director, and this appointment is at will and may be terminated at any time with or without cause.

• This position is subject to the financial disclosure requirements of the California Political Reform Act of 1974. The successful candidate for this position will be required to file financial interest statements upon assuming this position, annually while holding this position, and when leaving this position.

• Work will be primarily performed at: Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA.


How To Apply

Apply directly online at and follow the on-line instructions to complete the application process.


About Berkeley Lab

Berkeley Lab is a U.S. Department of Energy (DOE) national laboratory managed by the University of California and designated a Federally Funded Research and Development Center. The Laboratory conducts world-class research that supports clean energy, a healthy planet, and solution-inspired discovery science. Berkeley Lab is defined by our deeply felt sense of stewardship, which we describe as a commitment to taking care of the Laboratory's research, people, and resources that are entrusted to us. Our values of team science, innovation, service, trust, and respect knit us together as a community. We practice these values and prioritize our principles of inclusion, diversity, equity, and accountability (IDEA) to build highly effective teams that produce world-class science and technology and where all individuals, regardless of their backgrounds, disciplines, and experiences, can thrive. More about Berkeley Lab.


Based on University of California Policy - SARS-CoV-2 (COVID-19) Vaccination Program and U.S Federal Government requirements, Berkeley Lab requires that all members of our community obtain the COVID-19 vaccine as soon as they are eligible. As a condition of employment at Berkeley Lab, all Covered Individuals must Participate in the COVID-19 Vaccination Program by providing proof of Full Vaccination or submitting a request for Exception or Deferral. Visit for more information.


Berkeley Lab is committed to Inclusion, Diversity, Equity and Accountability (IDEA, and strives to continue building community with these shared values and commitments. Berkeley Lab is an Equal Opportunity and Affirmative Action Employer. We heartily welcome applications from women, minorities, veterans, and all who would contribute to the Lab's mission of leading scientific discovery, inclusion, and professionalism. In support of our diverse global community, all qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, age, or protected veteran status.


Equal Opportunity and IDEA Information Links:

Know your rights, click here ( for the supplement: Equal Employment Opportunity is the Law and the Pay Transparency Nondiscrimination Provision ( under 41 CFR 60-1.4.

Tags: Biology Classification Computer Science Data management Engineering Finance Machine Learning Mathematics PHP Physics Research Security

Perks/benefits: Career development Conferences Equity Transparency

Region: North America
Country: United States

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