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Data Science Jobs in Hawaii (NOW HIRING)

ManTech International

Data Scientist

Aiea, HI · On-site

$141K - $236K/yr

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or related field * 9+ years of relevant experience, including 4+ years leading data science initiatives and developing ...

Booz Allen Hamilton

OSINT Data Scientist

Honolulu, HI

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world impact. You'll work closely with your clients to understand their questions and needs, and then dig into ...

Booz Allen Hamilton

OSINT Data Scientist

Honolulu, HI · On-site

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world impact. You'll work closely with your clients to understand their questions and needs, and then dig into ...

Booz Allen Hamilton, Inc.

OSINT Data Scientist

Honolulu, HI · On-site

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world impact. You'll work closely with your clients to understand their questions and needs, and then dig into ...

Booz Allen Hamilton, Inc.

OSINT Data Scientist

Honolulu, HI · On-site +1

$77K - $176K/yr

On our team, you'll use your analytical skills and data science knowledge to create real-world impact. You'll work closely with your clients to understand their questions and needs, and then dig into ...

National Capitol Contracting (NCC)

Be Seen First

Senior Data Scientist

Honolulu, HI · On-site

Bachelor's degree in Data Science, Computer Science, Information Systems, Statistics, Mathematics, Engineering, or a related technical field. * 9+ years of experience in data analytics, business ...

MANTECH

Data Scientist with Security Clearance

Aiea, HI · On-site

Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or related field * 9+ years of relevant experience, including 4+ years leading data science initiatives and developing ...

Cymertek

Data Scientist

Honolulu, HI · On-site

DEGREE (Level Desired) Bachelor's Degree DEGREE (Focus) Computer Science, Data Science, Statistics, Mathematics, Applied Mathematics, Engineering, Economics, Physics, Operations Research, Information ...

Cymertek

Data Scientist

Honolulu, HI · On-site

DEGREE (Level Desired) Bachelor's Degree DEGREE (Focus) Data Science, Computer Science, Statistics, Mathematics, Artificial Intelligence, Machine Learning, Information Systems, Operations Research ...

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All JobsData Science JobsData Science Jobs in Hawaii

Data Science information

See Hawaii salary details

$39K

$127.5K

$204.2K

How much do data science jobs pay per year?

As of Jul 17, 2026, the average yearly pay for data science in Hawaii is $127,520.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,300.00 and $141,300.00 per year, depending on experience, location, and employer.

Is data science a good career?

Data science is a growing field with high demand for professionals skilled in statistics, programming, and data analysis tools like Python and R. It offers competitive salaries, diverse industry applications, and opportunities for advancement, making it a strong career choice for those with relevant skills and education.

What are the key skills and qualifications needed to thrive as a Data Scientist, and why are they important?

To thrive as a Data Scientist, you need a strong background in statistics, programming (often Python or R), and data analysis, usually supported by a degree in a quantitative field. Familiarity with machine learning libraries (like scikit-learn or TensorFlow), big data tools (such as Hadoop or Spark), and data visualization platforms is typically required. Critical thinking, problem-solving, and effective communication are vital soft skills for translating complex data insights into actionable business strategies. These skills and qualities are essential for extracting value from data, driving informed decisions, and effectively collaborating with multidisciplinary teams.

Is 40 too late for data science?

Data science is a field open to individuals of all ages, and many professionals transition into it later in their careers. Success often depends on acquiring relevant skills such as programming, statistics, and machine learning, which can be learned through online courses, bootcamps, or degrees regardless of age.

What are some common challenges faced by data scientists when working with real-world datasets?

Data scientists often encounter challenges such as missing or inconsistent data, unstructured formats, and noisy information in real-world datasets. Cleaning and preprocessing data to ensure its quality can be time-consuming but is critical for building accurate models. Additionally, data scientists may work closely with domain experts and other team members to better understand the data's context and ensure their analyses align with business objectives. Overcoming these challenges requires strong problem-solving skills and effective collaboration within cross-functional teams.

What is data science?

Data science is an interdisciplinary field that uses scientific methods, algorithms, and systems to extract insights and knowledge from structured and unstructured data. It combines skills from statistics, computer science, and domain expertise to analyze and interpret complex data sets. Data scientists work with large amounts of data to identify patterns, make predictions, and help organizations make data-driven decisions.

What jobs can a Data Scientist do?

A Data Scientist can work in roles such as data analyst, machine learning engineer, data engineer, or business intelligence analyst. These roles involve analyzing large datasets, developing predictive models, and using tools like Python, R, and SQL to support decision-making across various industries.

What is the difference between Data Science vs Data Analyst?

AspectData ScienceData Analyst
Required skillsStatistics, programming (Python, R), machine learningData visualization, SQL, basic statistics
Work environmentDeveloping models, predictive analytics, researchReporting, data cleaning, descriptive analysis
Tools usedPython, R, Jupyter, TensorFlowExcel, SQL, Tableau, Power BI
Industry usageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Data Science and Data Analyst roles often overlap but differ mainly in scope. Data Scientists focus on building predictive models and advanced analytics, requiring programming and machine learning skills. Data Analysts primarily handle data cleaning, reporting, and visualization. Both roles are essential in data-driven industries, but Data Science is more technical and research-oriented, while Data Analysis emphasizes interpreting data for business insights.

What work do you do as a Data Scientist?

A Data Scientist analyzes large datasets to extract insights, build predictive models, and inform business decisions. They use programming languages like Python or R, and tools such as SQL and machine learning frameworks, often working in collaborative environments with data engineers and analysts.

What Does a Data Scientist Do?

As a Data Scientist, you are qualified to work in such diverse fields as research and development, politics, advertising and marketing, technology, healthcare, government, and higher education as well as multiple others. In general, your duties and responsibilities will be to compile and analyze relevant statistics and turn those numbers into algorithms that reveal insights that can be used by other researchers in their areas of study. Data Science can reveal things like consumer buying habits or the likelihood of success for a course of action. Other duties might vary, depending on your unique field of specialty. Related areas in which a Data Scientist might wish to focus include work as a Data Analyst, Machine Learning Engineer, and Project Manager.
More about Data Science jobs
What are the most commonly searched types of Data Science jobs in Hawaii? The most popular types of Data Science jobs in Hawaii are:
What are popular job titles related to Data Science jobs in Hawaii? For Data Science jobs in Hawaii, the most frequently searched job titles are:
What job categories do people searching Data Science jobs in Hawaii look for? The top searched job categories for Data Science jobs in Hawaii are:
What cities in Hawaii are hiring for Data Science jobs? Cities in Hawaii with the most Data Science job openings:
Data Science jobs near you
Infographic showing various Data Science job openings in Hawaii as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 14% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $127,520 per year, or $61.3 per hour.

Data Scientist 2 with Security Clearance

GRVTY

Honolulu, HI • On-site

Other

Re-posted 13 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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