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Bs Computer Science Jobs in Hawaii (NOW HIRING)

GRVTY

Data Scientist 2

Honolulu, HI · On-site

$125K - $155K/yr

Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field ...

GRVTY

Data Scientist 2

Honolulu, HI

$125K - $155K/yr

Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field ...

Clear Ridge Defense

Data Scientist (Hawaii)

Wahiawa, HI · On-site

$98K - $215K/yr

A Bachelor's Degree in a Computer Science/Mathematics related field. * An ability to work in a fast-paced and dynamic workplace with unique TTPs. Nice-To-Haves * Leadership experience. Additional ...

Clear Ridge Defense

Data Scientist (Hawaii)

Wahiawa, HI · On-site

$98K - $215K/yr

A Bachelor's Degree in a Computer Science/Mathematics related field. * An ability to work in a fast-paced and dynamic workplace with unique TTPs. Nice-To-Haves * Leadership experience. Additional ...

IntelliGenesis

Data Scientist Level 3

Waimanalo, HI · On-site

... computer science, and application-specific knowledge * Through analytic modeling, statistical ... Minimum of ten (10) years of relevant experience and a Bachelor's degree or twelve (12) years of ...

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All JobsBs Computer Science JobsBs Computer Science Jobs in Hawaii

Bs Computer Science information

See Hawaii salary details

$58.7K

$86.3K

$101.8K

How much do bs computer science jobs pay per year?

As of Jun 10, 2026, the average yearly pay for bs computer science in Hawaii is $86,347.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,500.00 and $97,100.00 per year, depending on experience, location, and employer.

What is a BS in Computer Science?

A BS in Computer Science is a Bachelor of Science degree that focuses on the theoretical foundations and practical applications of computing and programming. Students learn about algorithms, data structures, software development, computer systems, and sometimes topics like artificial intelligence, cybersecurity, and databases. Graduates are prepared for careers in software engineering, IT, research, or for further study in graduate programs. The degree generally takes about four years to complete and combines coursework, projects, and sometimes internships to provide a comprehensive understanding of computer science.

What are the key skills and qualifications needed to thrive as a Computer Science graduate, and why are they important?

To thrive as a Computer Science graduate, you need strong analytical thinking, programming proficiency, and a solid grasp of algorithms and data structures, typically supported by a bachelor's degree in computer science or a related field. Familiarity with coding languages (such as Python, Java, or C++), version control systems like Git, and knowledge of software development methodologies are highly valued. Effective problem-solving, teamwork, and communication skills help you excel in collaborative and dynamic tech environments. These capabilities enable you to design, develop, and maintain robust software solutions that meet real-world needs.

What types of entry-level roles are commonly available to graduates with a BS in Computer Science, and how can I identify which path aligns with my interests?

Graduates with a BS in Computer Science often find entry-level opportunities as software developers, QA engineers, data analysts, IT support specialists, or web developers. To determine which path best suits your interests, consider the subjects you enjoyed most during your studies, such as programming, databases, or networking, and look for roles that emphasize those skills. Internships, personal projects, and participation in coding communities can also provide valuable insight into various specializations, helping you make a more informed decision as you start your career.

What is the difference between Bs Computer Science vs Bs Information Technology?

AspectBs Computer ScienceBs Information Technology
Core FocusProgramming, algorithms, software development, theoretical foundationsIT infrastructure, network management, systems administration
CertificationsComputer Science-related certifications (e.g., Cisco, Microsoft)IT certifications (e.g., CompTIA, Cisco)
Work EnvironmentSoftware companies, tech startups, research labsCorporate IT departments, network operations centers
Industry UsageSoftware development, research, academiaIT support, network management, system administration

While both degrees prepare students for tech careers, Bs Computer Science emphasizes programming and software development, whereas Bs Information Technology focuses on managing and supporting IT systems and networks. Your choice depends on whether you prefer coding and software design or IT infrastructure management.

What are popular job titles related to Bs Computer Science jobs in Hawaii? For Bs Computer Science jobs in Hawaii, the most frequently searched job titles are:
What job categories do people searching Bs Computer Science jobs in Hawaii look for? The top searched job categories for Bs Computer Science jobs in Hawaii are:
Bs Computer Science jobs near you
Infographic showing various Bs Computer Science job openings in Hawaii as of June 2026, with employment types broken down into 1% As Needed, 93% Full Time, 5% Part Time, and 1% Nights. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $86,347 per year, or $41.5 per hour.

Data Scientist 2 with Security Clearance

GRVTY

Honolulu, HI

Other

Posted 5 days ago

Job description

What You'll be Owning: * We are actively searching for Data Scientists, located in Hawaii, to support our team. We have varying levels of Data Scientist roles, depending on years of experience and education. * Performs tasks associated with Big Data Platform management, utilizes skills in programming languages, develops prototype algorithms as well as algorithm refinements, and supports data visualization and analytics.

What You Must Have : * Bachelor's Degree with 3 years of relevant experience OR Associates degree with 5 years of relevant experience * Bachelor's Degree must be in Mathematics, Applied Mathematics Statistics, Applied Statistics, Machine learning, Data Science, Operations Research, or Computer Science or a degree in a related field (Computer Information Systems, Engineering), a degree in the physical/hard sciences (e.g. physics, chemistry, biology, astronomy), or other science disciplines with a substantial computational component (i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g.

algorithms, programming, , data structures, data mining, artificial intelligence). College-level requirements, or upper-level math courses designated as elementary or basic do not count. Note: A broader range of degrees will be considered if accompanied by a Certificate in Data Science from an accredited college/university.

* Relevant experience must be in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python)), statistical analysis (e.g., variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g., data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering. Experience in more than one area is strongly preferred * Active TS/SCI w/poly What Would Be Nice to Have: * Foundations: (Mathematical, Computational, Statistical) 2. Data Processing: (Data management and curation, data description and visualization, workflow, and reproducibility) * Modeling, Inference, and Prediction: (Data modeling and assessment, domain-specific considerations) * Devise strategies for extracting meaning and value from large datasets.

Make and communicate principled conclusions from data using elements of mathematics, * Statistics, computer science, and application specific knowledge. * Through analytic modeling, statistical analysis, programming, and/or another appropriate scientific method, develop and implement qualitative and quantitative methods for characterizing, exploring, and assessing large datasets in various states of organization, cleanliness, and structure that account for the unique features and limitations inherent in data holdings. * Translate practical mission needs and analytic questions related to large datasets into technical requirements and, conversely, assist others with drawing appropriate conclusions from the analysis of such data.

Effectively communicate complex technical information to non-technical audiences. Make informed recommendations regarding competing technical solutions by maintaining awareness of the constantly shifting, processing, storage and analytic capabilities and limitations.

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