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Data Science Jobs in Hawaii (NOW HIRING)

Data Engineer

Honolulu, HI

$113K - $135K/yr

KBR's work is at the forefront of engineering, logistics, operations, science, program management ... As a Data Engineer, you will be a critical part of the team that is responsible for enabling the ...

Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics). * Minimum of 5 years of hands-on experience in big data analysis and data-driven ...

Data Engineer with Security Clearance

Honolulu, HI · On-site

$113K - $135K/yr

KBR's work is at the forefront of engineering, logistics, operations, science, program management ... As a Data Engineer, you will be a critical part of the team that is responsible for enabling the ...

Assessments Data Scientist

Aiea, HI · On-site

$103K - $125K/yr

Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics). * Minimum of 5 years of hands-on experience in big data analysis and data-driven ...

$90/hr

Collaborate with multi-disciplinary teams including OSINT analysts, data scientists, and operations personnel * Additional duties as assigned or required What we are looking for * 9 years relevant ...

Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics). * Minimum of 5 years of hands-on experience in big data analysis and data-driven ...

Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics). * Minimum of 5 years of hands-on experience in big data analysis and data-driven ...

Data Modeler

Honolulu, HI · On-site

$54 - $70.25/hr

DEGREE (Level Desired) Bachelor's Degree DEGREE (Focus) Computer Science, Information Systems, Data Science, Database Management, Software Engineering, Mathematics, Statistics, Engineering, Business ...

SIMILAR CAREER TITLES Business Analyst, Data Scientist, Data Engineer, Financial Analyst, Marketing Analyst, Operations Analyst, Reporting Analyst, Insights Analyst, Research Analyst, Quantitative ...

Bachelor's degree in data science, computer science, artificial intelligence, machine learning, mathematics, or related technical field with 8+ years of experience (advanced degree equivalency ...

Collaborate with engineering, product, and data science teams to understand requirements, incorporate stakeholder feedback, and deliver AI/ML solutions that address business and technical needs.

Showing results 41-60

Data Science information

See Hawaii salary details

$39K

$127.5K

$204.2K

How much do data science jobs pay per year?

As of Aug 7, 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 a data scientist in high demand?

Yes, data scientists are in high demand across many industries due to the increasing reliance on data-driven decision making. The role requires skills in programming, statistics, and machine learning, and job growth is expected to continue as organizations expand their data capabilities.

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.

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 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 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.
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:
Infographic showing various Data Science job openings in Hawaii as of August 2026, with employment types broken down into 100% Full Time. Highlights an 80% In-person, 4% Hybrid, and 16% Remote job distribution, with an average salary of $127,520 per year, or $61.3 per hour.

$113K - $135K/yr

Full-time

Re-posted 10 days ago


KBR rating

8.3

Company rating: 8.3 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

136th of 441 rated engineering


Job description

Title:

Data Engineer

Belong. Connect. Grow. with KBR!

KBR's National Security Solutions team provides high-end engineering and advanced technology solutions to our customers in the intelligence and national security communities. In this position, your work will have a profound impact on the country's most critical role - protecting our national security.

Why Join Us?

  • Innovative Projects: KBR's work is at the forefront of engineering, logistics, operations, science, program management, mission IT and cybersecurity solutions.
  • Collaborative Environment: Be part of a dynamic team that thrives on collaboration and innovation, fostering a supportive and intellectually stimulating workplace.
  • Impactful Work: Your contributions will be pivotal in designing and optimizing defense systems that ensure national security and shape the future of space defense.

Come join the ITEA award winning TRMC BDKM team and be a part of the team responsible for revolutionizing how analysis is performed across the entire Department of Defense!

Key Responsibilities:

As a Data Engineer, you will be a critical part of the team that is responsible for enabling the development of data-driven decision analysis products through the innovative application, and promotion, of novel methods from data science, machine learning, and operations research to provide robust and flexible testing and evaluation capabilities to support DoD modernization.

  • Analytic Experience: Candidate will be a part of the technical team responsible for providing analytic consulting services, supporting analytic workflow and product development and testing, promoting the user adoption of methods and best practices from data science, conducting applied methods projects, and supporting the creation of analysis-ready data.
  • Onsite Support: Candidate will be the face of the CHEETAS Team and will be responsible for ensuring stakeholders have the analytical tools, data products and reports they need to make insightful recommendations based on your data driven analysis.
  • Stakeholder Assistance: Candidate will directly assisting both analyst / technical and non-analyst / non-technical stakeholders with the analysis of DoD datasets and demonstrating the 'art of the possible' to the stakeholders and VIPs with insights gained from your analysis of DoD Test and Evaluation (T&E) data.
  • Communication: Must effectively communicate at both a programmatic and technical level. Although you potentially may be the only team member physically on-site supporting you will not be alone.You will have support from other data science team members as well as the software engineering and system administration teams.
  • Technical Support: Candidate will be responsible for running and operating CHEETAS (and other tools); demonstrating these tools to stakeholders & VIPs; conveying analysis results; adapting internally-developed tools, notebooks and reports to meet emerging needs; gathering use cases, requirements, gaps and needs from stakeholders and for larger development items providing that information as feature requests or bug reports to the CHEETAS development team; and performing impromptu hands-on training sessions with end users and potentially troubleshooting problems from within closed networks without internet access (with support from distributed team members).
  • Independent Work: Candidate must be self-motivated and capable of working independently with little supervision / direct tasking.

Work Environment:

  • Location: Onsite; Honolulu, HI
  • Travel Requirements: This position will require travel of 25% with potential surge to 50% to support end users located at various DoD ranges & labs located across the US (including Alaska and Hawaii). When not supporting a site, this position can work remotely or from a nearby KBR office (if available and desired).
  • Working Hours: Standard, although you potentially may be the only team member physically on-site providing support, you will not be alone.

Basic Qualifications:

  • Security Clearance: Active or current TS/SCI Clearance is required
  • Education: A degree in operations research, engineering, applied math, statistics, computer science or information technology with preferred 15+ years of experience within DoD. Candidates with 10-15 years of DoD experience will be considered on a case-by-case basis. Entry level candidates will not be considered.
  • Technical Experience: Previous experience must include five (5) years of hands-on experience in big data analytics, five (5) years of hands-on experience with object-oriented and functional languages (e.g., Python, R, C++, C#, Java, Scala, etc.).
  • Data Experience: Experience in dealing with imperfections in data. Experience should demonstrate competency in key concepts from software engineering, computer programming, statistical analysis, data mining algorithms, machine learning, and modeling sufficient to inform technical choices and infrastructure configuration.
  • Data Analytics: Proven analytical skills and experience in preparing and handling large volumes of data for ETL processes. Experience should include working with teams in the development and interpretation the results of analytic products with DoD specific data types.
  • Big Data Infrastructure: Experience in the installation, configuration, and use of big data infrastructure (Spark, Trino, Hadoop, Hive, Neo4J, JanusGraph, HBase, MS SQL Server with Polybase, VMWare as examples). Experience in implementing Data Visualization solutions.

Qualifications Required:

  • Experience using scripting languages (Python and R) to process, analyze and visualize data.
  • Experience using notebooks (Jupyter Notebooks and RMarkdown) to create reproducible and explainable products.
  • Experience using interactive visualization tools (RShiny, pyShiny, Dash) to create interactive analytics.
  • Experience generating and presenting reports, visualizations and findings to customers.
  • Experience building and optimizing 'big data' data pipelines, architectures and data sets.
  • Experience cleaning and preparing time series and geospatial data for analysis.
  • Experience working with Windows, Linux, and containers.
  • Experience querying databases using SQL and working with and configuring distributed storage and computing environments to conduct analysis (Spark, Trino, Hadoop, Hive, Neo4J, JanusGraph, MongoDB, Accumulo, HBase as examples).
  • Experience working with code repositories in a collaborative team.
  • Ability to make insightful recommendations based on data driven analysis and customer interactions.
  • Ability to effectively communicate both orally and in writing with customers and teammates.
  • Ability to speak and present findings in front of large technical and non-technical groups.
  • Ability to create documentation and repeatable procedures to enable reproducible research.
  • Ability to create training and educational content for novice end users on the use of tools and novel analytic methods.
  • Ability to solve problems, debug, and troubleshoot while under pressure and time constraints is required.
  • Should be self-motivated to design, develop, enhance, reengineer or integrate software applications to improve the quality of data outputs available for end users.
  • Ability to work closely with data scientists to develop and subsequently implement the best technical design and approach for new analytical products.
  • Strong analytical skills related to working with both structured and unstructured datasets.
  • Excellent programming, testing, debugging, and problem-solving skills.
  • Experience designing, building, and maintaining both new and existing data systems and solutions
  • Understanding of ETL processes, how they function and experience implementing ETL processes required.
  • Knowledge of message queuing, stream processing and extracting value from large disparate datasets.
  • Knowledge of software design patterns and Agile Development methodologies is required.
  • Knowledge of methods from operations research, statistical and machine learning, data science, and computer science is sufficient to select appropriate methods to enable data preparation and computing architecture configuration to implement these approaches.
  • Knowledge of computer programming concepts, data structures and storage architecture, to include relational and non-relational databases, distributed computing frameworks, and modeling and simulation experimentation sufficient to select appropriate methods to enable data preparation and computing architecture configuration to implement these approaches.

Basic Compensation:

$119,900 - $179,000

This range is for the Hawaii area only

The offered rate will be based on the selected candidate's knowledge, skills, abilities and/or experience and in consideration of internal parity.

Additional Compensation:

KBR may offer bonuses, commissions, or other forms of compensation to certain job titles or levels, per internal policy or contractual designation. Additional compensation may be in the form of sign on bonus, relocation benefits, short term incentives, long term incentives, or discretionary payments for exceptional performance.

Ready to Make a Difference?

If you're excited about making a significant impact in the field of space defense and working on projects that matter, we encourage you to apply and join our team at KBR. Let's shape the future together.

Belong, Connect and Grow at KBR
At KBR, we are passionate about our people and our Zero Harm culture. These inform all that we do and are at the heart of our commitment to, and ongoing journey toward being a People First company. That commitment is central to our team of team's philosophy and fosters an environment where everyone can Belong, Connect and Grow. We Deliver - Together.

KBR is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, disability, sex, sexual orientation, gender identity or expression, age, national origin, veteran status, genetic information, union status and/or beliefs, or any other characteristic protected by federal, state, or local law.


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About KBR

Sourced by ZipRecruiter

At KBR, we partner with government and industry clients to provide purposeful and comprehensive solutions with an emphasis on efficiency and safety. With a full portfolio of services, proprietary technologies and expertise, our employees are ready to handle projects and missions from planning and design to sustainability and maintenance. Whether at the bottom of the ocean or in outer space, our clients trust us to deliver the impossible on a daily basis.

Industry

It services

Company size

10,000+ Employees

Headquarters location

Houston, TX, US

Year founded

1998