Oceanography Data Science Research Specialist - 141464

The organizing principle of the Integrative Oceanography Division (IOD) resides in a shared commitment to collaborative, interdisciplinary science. “Integrative” denotes our philosophy that multiple approaches are important in creating a better understanding of the ocean system. We take great pride in our membership of physical, biological, chemical and geological oceanographers, climate and information scientists, data and information managers, engineers, technicians, education specialists, administrative and management professionals. IOD distinguishes itself as scientific home for researchers working at the boundaries of traditional academic spheres, and generating growing programs in the integration of research with informatics as well as with education and public outreach. From pelagic to benthic ecology, shoreline to open ocean dynamics, data to information systems, our research encompasses field work, laboratory experimentation and computer modeling to acquire, integrate, synthesize and understand diverse data sets to elucidate the underlying dynamics of complex, multidimensional ocean systems.

The Southern California Coastal Ocean Observing System (SCCOOS), the U.S. Integrated Ocean Observing System (IOOS) Regional Association for Southern California, was established in 2004 as a consortium of 9 universities and organizations and encompasses coastal areas from Morro Bay, California to Ensenada, Baja California. The mission is to produce, integrate, and communicate high-quality, science-based information to promote coastal ocean safety, resilience, and sustainability for all members of society. SCCOOS goals and objectives align closely with U.S. Integrated Ocean Observing System (IOOS) Enterprise 2022-2025 Strategic Plan (US IOOS, 2022) and support the U.S. IOOS seven societal goals (US IOOS, 2013) and seven societal needs (NOAA IOOS, 2026).

The Researcher applies computational, computer science, data science, and CI software research and development principles, with relevant domain science knowledge in Marine Sciences and Oceanography to lead and develop products for stakeholder and industry clients in ocean observing, along with professional programming concepts for medium-sized projects or portions of larger projects. Develops and optimizes a variety of computational, data science, and CI research tools and components in collaboration with the SCCOOS Data Management and Cyber-infrastructure team. Performs research on current and future HPC, data, and CI technologies, hardware and software projects in collaboration with the SCCOOS Data Management team and seeks data science solutions to end-user requests for specific operational or decision-making tools. Engages with diverse communities to understand and implement data solutions for ocean and climate services. Works on algorithm development, optimization, programming, performance analysis and / or benchmarking assignments of moderate scope where the tasks involve knowledge of Marine Science, Oceanography, and Environmental Science.

• Must be willing to work non-standard hours, including weekends if necessary.

• Advanced skills associated with programming design, modification and implementation for ocean science applications.
• Familiarity with logical data design and data mapping or data conversion. Ability to convert SCCOOS datasets from their native format to netCDF/THREDDS and or MYSQL.
• Thorough experience working in a complex computing / data / CI environment encompassing all or some of the following: HPC, data science infrastructure and tools / software, and diverse domain science application base.
• Proven skills and experience in independently resolving broad computing / data / CI problems using introductory and / or intermediate principles.
• Experience with some or all of the following programming languages, platforms, and applications: Python, GitHub, MATLAB, R/R Studio, JavaScript, SQL, Shell, XML, KML, EML, and Google EarthEngine.
• Demonstrated ability to contribute research and technical content to grant proposals.
• Advanced skills, and demonstrated experience associated with one or more of the following: HPC hardware and software power and performance analysis and research, design, modification, Implementation and deployment of HPC or data science or CI applications and tools.
• Works independently and as part of a team. Demonstrated problem-solving skills. Ability to learn effectively and meet deadlines. Ability to work within the national IOOS program system schedules and timelines. Ability to coordinate within the multiple IOOS regions for problem-solving on the local, regional and national scale.
• Demonstrated broad experience in one or more of the following: optimizing, benchmarking, HPC performance and power modeling, analyzing hardware, software, and applications for HPC / data / CI.
• Proven ability to understand research computing / data / CI needs, mapping use cases to requirements and how systems / software / infrastructure can support those needs and meet the requirements. Demonstrated ability to develop and implement such solutions.
• Bachelor’s degree in Marine/Environmental Sciences/Oceanography with computer / computational / data specialization or equivalent combination of education and experience.
• Intermediate knowledge of HPC / data science / CI.
• Demonstrated ability to regularly interface with management. The ability and willingness to work across agencies and organizations to accomplish tasks, respond to agency needs, and meet user requirements.
• Demonstrated effective communication and interpersonal skills. Demonstrated ability to communicate technical information to technical and non-technical personnel at various levels in the organization and to external research and education audiences.
• Ability to design and conduct user interface tutorials for stakeholders/end-users. Ability to communicate through oral and written presentations the SCCOOS data management system and its various components at local, regional and national meetings. Ability to communicate with diverse audiences of all ages.
• Self-motivated and works independently and as part of a team. Able to learn effectively and meet deadlines.
• Proven ability to successfully work on multiple concurrent projects.
• Demonstrated experience and ability to collaborate effectively with all levels of staff; technical, students, faculty and administrators

SPECIAL CONDITIONS

• Job offer is contingent upon satisfactory clearance based on Background Check results.

Factors in determining the appropriate compensation for a role include experience, skills, knowledge, abilities, education, licensure and certifications, and other business and organizational needs. The Hiring Pay Scale referenced in the job posting is the budgeted salary or hourly range that the University reasonably expects to pay for this position. The Annual Full Pay Range may be broader than what the University anticipates to pay for this position, based on internal equity, budget, and collective bargaining agreements (when applicable).

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