Biological Data Analyst Jobs (NOW HIRING)

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.

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.

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.

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 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)

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)

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