Scientific Data Engineer

Lawrence Berkeley National Laboratory; Berkeley, Northern (CA, KY); Hybrid; USD 132,000 - 161,000; Full time

Benefits offered by this job

Health and retirement benefits

Job summary

Lawrence Berkeley National Laboratory is seeking a Scientific Data Engineer in the Scientific Data Division. The role focuses on multi-modal data modeling and analysis for bioscience, integrating data management and ML technologies to enable scientific knowledge discovery.

You will work with omics/structural biology and neurophysiology data, contributing to FAIR data science and modern data understanding within a cross-disciplinary team.

Qualifications

• Minimum of 5 years of related experience with a Bachelor’s degree in computer science, data science, machine learning, bioinformatics, or equivalent; or 3 years and a Master’s degree; or equivalent work experience designing and developing software for data modeling or analysis
• Experience developing software in a scientific or research context, such as a research group or scientific user facility
• Hands-on experience in a production environment, developing scientific software or data pipelines
• Experience contributing to community-driven open source software
• Experience in data management, scientific data analysis, or machine learning
• Strong teamwork and communication skills
• Experience with Git and CI systems (GitHub/GitLab)
• Ability to translate domain scientist requirements into technical designs

Responsibilities

• Design and develop software packages for scientific data management and analysis
• Work with domain experts to develop FAIR data models for bioscience applications
• Support ML/AI use of biological data by structuring, documenting, and making it accessible
• Maintain and manage open source software projects with CI, testing, and releases
• Design and maintain HPC and cloud solutions for visualization and analysis of complex data
• Develop ML/AI solutions for biological data in collaboration with scientists
• Train scientists and research software engineers in using the software products
• Exercise judgment in selecting methods for obtaining solutions
• Network with senior internal and external personnel in their area of expertise

Skills

Software development

Data modeling

Machine learning

Collaboration

Git & CI

Education

Bachelor’s degree in Computer Science, data science, ML, bioinformatics, or equivalent

Tools

HDF5

Zarr

MongoDB

PostgreSQL

Redis

Neurodata Without Borders

LinkML

Job description

Lawrence Berkeley National Laboratory is hiring a Scientific Data Engineer within the Scientific Data Division.

The Computational Biosciences Group has an immediate opening for a software and data engineer in the area of multi-modal data modeling and analysis with applications to bioscience research. You will develop new methods and software tools that enable scientific knowledge discovery using modern data management and machine learning technologies and advance the state-of-the-art in data-intensive analysis. Your projects will focus on the domains of omics/structural biology data and neurophysiology data. Under limited instruction, you will be part of an experienced team conducting R&D in the areas of FAIR data science, AI, and modern methods for data understanding. You will be working as part of a multi-disciplinary team composed of computer scientists, data scientists, and bioinformaticians. Please note this is a scientific software/data engineering position– it is not a pure machine learning or AI research position, and it is not a pure data science or analytics position.

You will:

• Design and develop user-friendly software packages for scientific data management and analysis
• Work with domain experts to develop FAIR data models (i.e., models of the structure organization of the data) and management solutions for bioscience applications
• Support machine learning and AI use of biological data by making it well-structured, documented, and efficiently accessible
• Maintain and manage open source software products, including managing development priorities, software releases, continuous integration, and testing
• Design, implement and maintain high performance computing and cloud solutions for visualization and analysis of complex biological data
• Develop machine learning and AI solutions for analysis of biological data in close collaboration with diverse teams of scientists
• Train scientists and research software engineers in the use of the developed software products at workshops and conferences
• Demonstrate good judgment in selecting methods and techniques for obtaining solutions.
• Network with senior internal and external personnel in their own area of expertise.

We are looking for:

• Typically requires a minimum of 5 years of related experience with a Bachelor’s degree in computer science, data science, machine learning, bioinformatics, or equivalent; or 3 years and a Master’s degree; or equivalent work experience designing and developing software for data modeling or analysis; or a PhD in a relevant STEM field
• Demonstrated experience developing software in a scientific or research context, such as in a research group, a scientific user facility, or on a scientific software project
• Demonstrated hands-on experience in a production environment, developing scientific software, scientific data models, or scientific data pipelines
• Experience contributing to community-driven open source software
• Demonstrated experience in one or more of the following areas: data management, scientific data analysis, machine learning
• Works well in a collaborative team environment
• Demonstrated capability with the Git version control and continuous integration systems, such as GitHub or GitLab
• Ability to work effectively with domain scientists whose expertise is outside computing, and to translate their requirements into technical designs.
• Excellent oral and written communication skills.
• Demonstrated ability to work effectively as part of a cross-disciplinary team.

Desired skills/knowledge:

• Master’s or PhD in Computer Science or related field, with 5 or more years of professional experience designing and developing scientific data modeling or analysis software
• Experience working with modern scientific data formats and database systems, such as HDF5, Zarr, MongoDB, PostgreSQL, MySQL, and Redis
• Experience with Neurodata Without Borders, LinkML, or similar software ecosystems
• Experience working with large biological data, such as in the areas of neurophysiology, microbiology, genomics, or protein design
• Experience designing or working with structured data models, schemas, ontologies, or data standards
• Familiarity with FAIR data principles, persistent identifiers, provenance, and controlled vocabularies and ontologies
• Experience preparing scientific datasets for use by machine learning pipelines or LLM-based agents
• Experience working with cloud object storage, cloud computing, High-Performance Computing, data lakehouse architecture, or containerization.
• Experience developing web-based graphical user interfaces (GUIs) or application programming interfaces (APIs) for scientific data analysis and management

We’re here for the same mission, to bring science solutions to the world. Join our team and YOU will play a supporting role in our goal to address global challenges! Have a high level of impact and work for an organization associated with 17 Nobel Prizes!

We invest in our employees by offering a total rewards package you can count on:

• Exceptional health and retirement benefits, including pension or 401K-style plans
• A culture where you’ll belong - we are invested in our teams!
• In addition to accruing vacation and sick time, we also have a Winter Holiday Shutdown every year.
• Parental bonding leave (for both mothers and fathers)

Additional information:

Appointment type: This is a full-time, 2 years, term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.

Salary range: The expected salary for this position is $131,760 - $161,064, which fits into the full salary of $117,132 - $197,676 depending upon the candidate’s skills, knowledge, and abilities. This includes education, certifications, and years of experience.

Background check: This position is 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.

Work modality: Work may be performed on-site, or hybrid. The primary location for this role is Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Work must be performed within the United States. A REAL ID or other acceptable form of identification is required to access Berkeley Lab sites (for more information click here ).

Want to learn more about working at Berkeley Lab? Please visit:

careers.lbl.gov

Equal Employment Opportunity Employer: The foundation of Berkeley Lab is our Stewardship Values: Team Science, Service, Trust, Innovation, and Respect; and we strive to build community with these shared values and commitments. Berkeley Lab is an Equal Opportunity Employer. We heartily welcome applications from all who could contribute to the Lab's mission of leading scientific discovery, excellence, and professionalism. In support of our rich 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, protected veteran status, or other protected categories under State and Federal law.

Misconduct Disclosure Requirement:

As a condition of employment, the final candidate who accepts an offer of employment will be required to disclose if they have been subject to any final administrative or judicial decisions within the last seven years determining that they committed any misconduct; or have filed an appeal of a finding of substantiated misconduct with a previous employer. For additional information, click here .

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