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Data Science Manager Jobs in Hawaii (NOW HIRING)

GRVTY

Data Scientist 2

Honolulu, HI · On-site

Performs tasks associated with Big Data Platform management, utilizes skills in programming ... Relevant experience must be in designing/implementing machine learning, data science, advanced ...

GRVTY

Data Scientist 2

Honolulu, HI · On-site

$125K - $155K/yr

Performs tasks associated with Big Data Platform management, utilizes skills in programming ... Statistics, computer science, and application specific knowledge. * Through analytic modeling ...

GRVTY

Data Scientist 2

Honolulu, HI · On-site

$125K - $155K/yr

Performs tasks associated with Big Data Platform management, utilizes skills in programming ... Statistics, computer science, and application specific knowledge. * Through analytic modeling ...

ManTech

Data Scientist

Aiea, HI

$141K - $236K/yr

Minimum Qualifications: * Bachelor's degree in Data Science, Computer Science, Statistics ... management, and customers, via email, phone, and or virtual communication, which may involve ...

ManTech International

Data Scientist

Aiea, HI · On-site

$141K - $236K/yr

Minimum Qualifications: * Bachelor's degree in Data Science, Computer Science, Statistics ... management, and customers, via email, phone, and or virtual communication, which may involve ...

IntelliGenesis LLC

Data Scientist Level 3

Waimanalo, HI · On-site

$88K - $121K/yr

Data Processing: (Data management and curation, data description and visualization, workflow, and ... Data science * Advanced analytical algorithms * Programming (skill in at least one high-level ...

National Capitol Contracting (NCC)

Be Seen First

Senior Data Scientist

Honolulu, HI · On-site

Extract, transform, and analyze data using SQL, Python, PostreSQL, and other data management tools ... Bachelor's degree in Data Science, Computer Science, Information Systems, Statistics, Mathematics ...

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

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Data Science Manager information

See Hawaii salary details

$32.2K

$100.9K

$178.7K

How much do data science manager jobs pay per year?

As of Jul 17, 2026, the average yearly pay for data science manager in Hawaii is $100,929.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,600.00 and $130,400.00 per year, depending on experience, location, and employer.

What are the primary responsibilities of a Data Science Manager on a day-to-day basis?

As a Data Science Manager, your daily responsibilities typically include overseeing a team of data scientists and analysts, setting project priorities, and ensuring the timely delivery of data-driven solutions. You will often collaborate with cross-functional teams, such as engineering, product, and business stakeholders, to define problems, scope solutions, and communicate analytical insights. Your role also involves mentoring team members, reviewing code and analysis, and driving best practices in data science methodologies. This position requires balancing technical project oversight with team leadership and strategic business alignment.

What is a Data Science Manager job?

A Data Science Manager leads a team of data scientists to develop and implement data-driven solutions for business challenges. They oversee project timelines, ensure the quality of data analysis, and collaborate with cross-functional teams to drive decision-making. In addition to technical expertise, they require strong leadership, communication, and strategic thinking skills. Their role bridges the gap between data science initiatives and business objectives, ensuring the team's work aligns with company goals.

Is 40 too late for data science?

Age is not a barrier to becoming a data science manager; many professionals transition into data science roles later in their careers. Success depends on relevant skills, experience, and continuous learning in areas like programming, statistics, and machine learning. Employers value diverse backgrounds and practical expertise regardless of age.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of results come from 20% of the efforts or data. Data scientists often use this principle to focus on the most impactful features, models, or data subsets to improve efficiency and outcomes in projects.

What is the role of a data science manager?

A data science manager oversees data science teams, guiding project priorities, setting strategic goals, and ensuring the effective use of data analysis and modeling techniques. They coordinate between technical staff and business stakeholders, often requiring skills in leadership, communication, and familiarity with tools like Python, R, or SQL. Their responsibilities include managing workflows, mentoring team members, and ensuring project deliverables align with organizational objectives.

How much do data scientist managers make?

Data Science Managers typically earn between $110,000 and $160,000 annually, with salaries varying based on experience, location, and company size. They often oversee teams of data scientists, coordinate projects, and require strong skills in analytics tools and leadership. Senior roles or those in high-cost areas can offer higher compensation.

What are the key skills and qualifications needed to thrive in the Data Science Manager position, and why are they important?

To thrive as a Data Science Manager, you need strong analytical skills, experience in machine learning and data analytics, and a background in statistics or computer science, often supported by an advanced degree. Familiarity with tools like Python, R, SQL, cloud platforms, and experience managing data science projects are highly valued, and certifications such as Certified Analytics Professional (CAP) can be advantageous. Excellent leadership, project management, and communication skills are crucial for guiding teams and translating technical findings for stakeholders. These abilities ensure effective team performance, successful project delivery, and the alignment of data science initiatives with organizational goals.

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 Manager jobs in Hawaii? For Data Science Manager jobs in Hawaii, the most frequently searched job titles are:
What job categories do people searching Data Science Manager jobs in Hawaii look for? The top searched job categories for Data Science Manager jobs in Hawaii are:
What cities in Hawaii are hiring for Data Science Manager jobs? Cities in Hawaii with the most Data Science Manager job openings:
Data Science Manager jobs near you
Infographic showing various Data Science Manager 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 $100,929 per year, or $48.5 per hour.

Data Scientist 2

GRVTY

Honolulu, HI • On-site

Other

Re-posted 4 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'sDegree 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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