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Python Certification Jobs in Hawaii (NOW HIRING)

Data Scientist Level 3

Waimanalo, HI · On-site

$55.16K - $121.25K/yr

Information Assurance Certification may be required * Minimum of ten (10) years of relevant ... Programming (skill in at least one high-level language (e.g., Python)) * Statistical analysis (e.g ...

Information Assurance Certification may be required * Minimum of ten (10) years of relevant ... Programming (skill in at least one high-level language (e.g., Python)) * Statistical analysis (e.g ...

Network Engineer SME

Honolulu, HI · Hybrid

$147.29K - $199.28K/yr

Familiarity with software-defined networking (SDN) and network automation (Ansible, Python). * Experience with satellite communications (SATCOM) and tactical edge networking. * ITIL v4 certification ...

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Python Certification information

See Hawaii salary details

$13

$60

$89

How much do python certification jobs pay per hour?

As of May 31, 2026, the average hourly pay for python certification in Hawaii is $60.91, according to ZipRecruiter salary data. Most workers in this role earn between $50.19 and $69.18 per hour, depending on experience, location, and employer.

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

To thrive as a Python Developer, you need strong proficiency in Python programming, a solid understanding of algorithms, data structures, and often a relevant degree in computer science or a related field. Familiarity with development frameworks (like Django or Flask), version control systems such as Git, and relevant Python certifications are commonly expected. Problem-solving ability, adaptability, and effective communication are valuable soft skills that set top candidates apart. These competencies enable developers to write efficient, maintainable code and collaborate well within development teams on complex projects.

What types of projects or tasks can I expect to work on after earning a Python certification?

After earning a Python certification, you can expect to work on a variety of projects, ranging from web application development to data analysis and automation tasks. Many teams utilize Python for scripting workflows, managing databases, building APIs, or developing machine learning models. The exact nature of your work will often depend on the industry and organization, but collaboration with other developers, data analysts, or IT professionals is common. Certified Python professionals are frequently trusted with higher responsibility, including contributing to code reviews and designing scalable solutions.

What is a Python certification and why is it important?

A Python certification is an official credential that demonstrates a person's proficiency and knowledge in the Python programming language. Earning a certification can help validate your skills to employers, making you stand out in the job market. It often covers topics such as syntax, data structures, algorithms, and usage of Python libraries. Obtaining a certification can also provide structured learning and boost your confidence in applying Python in real-world projects. While not always required, it can be particularly beneficial for those new to programming or seeking to advance their careers.

What is the difference between Python Certification vs Data Analyst?

AspectPython CertificationData Analyst
Required CredentialsCertification in Python programmingDegree in Data Science, Statistics, or related field
Work EnvironmentSoftware development, automation, scriptingData analysis, reporting, business insights
Industry UsageTech, finance, automationBusiness, marketing, finance
Search & Comparison IntentLearning Python skills, certification benefitsUnderstanding roles, skills, and certifications for data analysis

Python Certification focuses on validating Python programming skills, often used in software development and automation. Data Analysts utilize Python for data manipulation and analysis but typically require a broader skill set including statistical knowledge and domain expertise. While Python Certification enhances technical credentials, Data Analyst roles emphasize a combination of technical and analytical skills. Both are valuable in data-driven industries, but they serve different career paths and skill requirements.

What are popular job titles related to Python Certification jobs in Hawaii? For Python Certification jobs in Hawaii, the most frequently searched job titles are:
What job categories do people searching Python Certification jobs in Hawaii look for? The top searched job categories for Python Certification jobs in Hawaii are:

Data Scientist 2 with Security Clearance

GRVTY

Honolulu, HI

Other

Posted 26 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.