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Data Science Project Manager Jobs in Hawaii (NOW HIRING)

HSI Mechanical, Inc.

Project Manager

Honolulu, HI · On-site

$100K - $130K/yr

The Project Manager will lead the project management team, including Project Superintendents ... Strong Mathematical and Scientific Aptitude : Proficient in mathematics, physical science, and ...

HSI Mechanical, Inc.

Project Manager

Honolulu, HI · On-site

$100K - $130K/yr

The Project Manager will lead the project management team, including Project Superintendents ... Strong Mathematical and Scientific Aptitude : Proficient in mathematics, physical science, and ...

TekSky

Project Manager

Kailua, HI · On-site

Four-year degree in physical, biological, geological, or related science * 5+ years of environmental consulting experience * Proven project management and client leadership experience * Strong ...

HSI Mechanical, Inc.

Project Manager

Honolulu, HI · On-site

$100K - $130K/yr

The Project Manager will lead the project management team, including Project Superintendents ... Strong Mathematical and Scientific Aptitude : Proficient in mathematics, physical science, and ...

Booz Allen Hamilton

Data Engineer

Honolulu, HI · On-site

$113K - $136K/yr

... projects in the industry. You'll deploy and develop pipelines and platforms that organize and make ... You'll use your experience in analytical exploration and data examination while you manage the ...

Booz Allen Hamilton

Data Engineer

Honolulu, HI · On-site

$113K - $135K/yr

... projects in the industry. You'll deploy and develop pipelines and platforms that organize and make ... You'll use your experience in analytical exploration and data examination while you manage the ...

Cymertek

Data Scientist

Honolulu, HI · On-site

DEGREE (Level Desired) Bachelor's Degree DEGREE (Focus) Computer Science, Data Science, Statistics ... Understanding of database management systems * Experience in deploying models to production

Amentum

Bachelor's Degree from an accredited college or university with a degree in Data Science, Information Systems, Information Technology, Cybersecurity, Knowledge Management, Project Management ...

KBR, Inc.

Data Engineer

Honolulu, HI · On-site

$113K - $135K/yr

Innovative Projects: KBR's work is at the forefront of engineering, logistics, operations, science ... management, mission IT and cybersecurity solutions. * Collaborative Environment: Be part of a ...

KBR

Data Engineer

Honolulu, HI · On-site

$113K - $135K/yr

Innovative Projects: KBR's work is at the forefront of engineering, logistics, operations, science ... management, mission IT and cybersecurity solutions. * Collaborative Environment: Be part of a ...

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All JobsData Science Project JobsData Science Project Manager JobsData Science Project Manager Jobs in Hawaii

Data Science Project Manager information

See Hawaii salary details

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$59

$83

How much do data science project manager jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for data science project manager in Hawaii is $59.75, according to ZipRecruiter salary data. Most workers in this role earn between $51.68 and $69.95 per hour, depending on experience, location, and employer.

What is a data science project manager?

A Data Science Project Manager is a professional who oversees and coordinates data science projects from inception to completion. They act as a bridge between technical data science teams and business stakeholders, ensuring that project goals align with organizational objectives. Responsibilities include planning project timelines, managing resources, mitigating risks, and communicating progress. They also help define project requirements, monitor deliverables, and ensure that outcomes meet quality standards. Strong communication, analytical, and organizational skills are essential for this role.

How does a data science project manager typically collaborate with data scientists and stakeholders throughout a project?

A Data Science Project Manager acts as a bridge between technical teams and business stakeholders, ensuring clear communication of goals, timelines, and deliverables. They facilitate regular meetings to discuss project progress, address any obstacles, and realign priorities as needed. By translating business requirements into actionable tasks for data scientists and providing updates to stakeholders, they help ensure that projects stay on track and deliver value. Effective collaboration often involves balancing technical feasibility with business needs, managing expectations, and fostering a cooperative team environment.

What is the difference between Data Science Project Manager vs Data Analyst?

AspectData Science Project ManagerData Analyst
Required CredentialsOften requires a bachelor’s or master’s in data science, analytics, or related fields; project management certifications beneficialTypically holds a bachelor’s degree in statistics, mathematics, or related areas; certifications like Microsoft Excel or Tableau are common
Work EnvironmentLeads data science projects, collaborates with data scientists, engineers, and stakeholdersAnalyzes data sets, creates reports, visualizations, and supports decision-making
Employer & Industry UsageUsed in tech, finance, healthcare, and consulting firms managing data science initiativesFound across industries for data reporting, business intelligence, and operational analysis

In summary, a Data Science Project Manager oversees data science projects and manages teams, requiring project management skills and relevant certifications. A Data Analyst focuses on analyzing data and creating reports, with a more technical and analytical role. Both roles are essential in data-driven organizations but differ in scope and responsibilities.

What are the key skills and qualifications needed to thrive as a data science project manager, and why are they important?

To thrive as a Data Science Project Manager, you need a solid understanding of data science methodologies, project management principles, and usually a degree in computer science, statistics, or a related field. Familiarity with analytics tools (such as Python, R, SQL), project management software (like Jira or Trello), and certifications such as PMP or Agile/Scrum are often required. Strong leadership, communication, and problem-solving skills set top performers apart by enabling effective team coordination and stakeholder management. These competencies ensure projects are delivered on time, within scope, and generate actionable insights that drive business value.
What are popular job titles related to Data Science Project Manager jobs in Hawaii? For Data Science Project Manager jobs in Hawaii, the most frequently searched job titles are:
What job categories do people searching Data Science Project Manager jobs in Hawaii look for? The top searched job categories for Data Science Project Manager jobs in Hawaii are:
Data Science Project Manager jobs near you
Infographic showing various Data Science Project Manager job openings in Hawaii as of August 2026, with employment types broken down into 88% Full Time, 11% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $124,277 per year, or $59.7 per hour.

Data Scientist 2 with Security Clearance

GRVTY

Honolulu, HI • On-site

Other

Re-posted 3 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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