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Fraud Detection Machine Learning Jobs in Hawaii (NOW HIRING)

Booz Allen Hamilton

Data Engineer

Honolulu, HI ยท On-site

$113K - $135K/yr

... including fraud detection and national intelligence. Responsibilities : โ€ข Overseeing the ... learning unfamiliar technologies, developing hands on proficiency, and guiding engineering teams ...

Cymertek Corporation

Cybersecurity Analyst

Honolulu, HI ยท On-site

... detection systems โ€ข Familiarity with malware analysis techniques โ€ข Ability to conduct forensic ... machine learning in cybersecurity โ€ข Knowledge of advanced penetration testing techniques โ€ข ...

Booz Allen Hamilton

$55K - $126K/yr

Knowledge of innovative cybersecurity capabilities, including AI and machine learning, Next ... We reserve the right to take your picture to verify your identity and prevent fraud. Candidate AI ...

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All JobsFraud Detection Machine Learning JobsFraud Detection Machine Learning Jobs in Hawaii

Fraud Detection Machine Learning information

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How much do fraud detection machine learning jobs pay per hour?

As of Jul 24, 2026, the average hourly pay for fraud detection machine learning in Hawaii is $18.76, according to ZipRecruiter salary data. Most workers in this role earn between $15.48 and $20.00 per hour, depending on experience, location, and employer.

What are some common challenges faced by professionals working in Fraud Detection Machine Learning, and how can they be addressed?

Professionals in Fraud Detection Machine Learning often face challenges such as dealing with highly imbalanced datasets, rapidly evolving fraud patterns, and the need for real-time detection. Managing data imbalance requires careful selection of evaluation metrics and specialized algorithms. Staying ahead of new fraud tactics involves continuous model retraining and close collaboration with domain experts. Additionally, integrating machine learning solutions with existing systems often requires cross-functional teamwork with IT, security, and compliance teams.

What is fraud detection using machine learning?

Fraud detection using machine learning involves leveraging algorithms and data analysis techniques to identify suspicious or fraudulent activities in various domains, such as banking, e-commerce, or insurance. These systems analyze large volumes of transaction data to detect patterns or anomalies that may indicate fraud. Machine learning models can adapt over time, improving their accuracy as they are exposed to more data. This approach helps organizations automate and enhance their ability to prevent, detect, and respond to fraudulent behavior efficiently.

What is the difference between Fraud Detection Machine Learning vs Fraud Analyst?

AspectFraud Detection Machine LearningFraud Analyst
CredentialsData science, machine learning certifications, programming skillsFinance, criminal justice degrees, analytical skills
Work EnvironmentData-driven, tech-focused, often in financial or e-commerce sectorsInvestigative, report-focused, in financial institutions or insurance companies
Employer & IndustryTech companies, banks, e-commerce platformsFinancial institutions, insurance firms, retail

Fraud Detection Machine Learning involves developing algorithms to identify fraudulent activities automatically, relying heavily on data analysis and programming. Fraud Analysts manually investigate suspicious cases and interpret data insights. While both roles aim to prevent fraud, Machine Learning specialists focus on building models, whereas Fraud Analysts focus on case investigation and decision-making.

What are the key skills and qualifications needed to thrive as a Fraud Detection Machine Learning Specialist, and why are they important?

To thrive as a Fraud Detection Machine Learning Specialist, you need strong expertise in machine learning, statistical analysis, and programming languages like Python or R, typically supported by a degree in computer science, data science, or a related field. Familiarity with tools such as TensorFlow, Scikit-learn, SQL databases, and experience with big data platforms or cloud services is highly valuable. Critical thinking, attention to detail, and effective communication are crucial soft skills for identifying complex fraud patterns and collaborating with interdisciplinary teams. These competencies are vital for developing accurate models that protect organizations from financial losses and maintain trust with customers.
What are popular job titles related to Fraud Detection Machine Learning jobs in Hawaii? For Fraud Detection Machine Learning jobs in Hawaii, the most frequently searched job titles are:
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What cities in Hawaii are hiring for Fraud Detection Machine Learning jobs? Cities in Hawaii with the most Fraud Detection Machine Learning job openings:
Fraud Detection Machine Learning jobs near you
Senior Data Scientist (Active Secret Clearance)

Senior Data Scientist (Active Secret Clearance)

Striveworks

Schofield Barracks, HI โ€ข On-site

$220K - $270K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted yesterday

Job description

"In 36 months, agentic AI systems will be an operating reality across major institutions. We intend to be central to it." - Dr. Jim Rebesco, Cofounder and CEO, Striveworks
The government's demand for AI is growing far faster than the systems required to support it. Fewer than 15% of federal AI programs have reached sustained production, despite billions of dollars invested. The models perform in testing, but they degrade in the real world. And when performance drops, trust goes with it.
Striveworks was built to solve that problem.
What you'll build
Since 2018, we have delivered the most trusted AI systems operating in real-world use cases-providing a layer of assurance underneath hundreds of deployed models that monitors performance, manages drift, and sustains systems long after they leave the lab.
As a Senior Data Scientist at Striveworks, you will be a core contributor to the projects, products, and direction of the company. Working as part of a team of data scientists, machine learning engineers, software engineers, and DevOps engineers, you'll develop and validate machine learning models and custom analytic algorithms applied to image, video, text, geospatial, time series, and structured data. You will also implement AI-based software solutions for cloud and edge environments. This role puts you directly at the customer site at Schofield Barracks, conducting mission-critical fieldwork and traveling internationally when the mission calls for it.
What it's like here
We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership-because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice.
What we're looking for
  • A BS degree in computer science, machine learning, mathematics, or a related discipline and 6+ years of relevant experience
  • Proficiency in machine learning and data science techniques, with experience applying them to text data
  • Proficiency in implementing and analyzing data structures and algorithms
  • Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn
  • Experience developing anomaly detection algorithms for AI systems, models, data, and workflows
  • Exposure to software development life cycle and tools
  • Active Secret (or above) US security clearance and US citizenship

The following isn't required, but we'd love to see it:
  • An advanced degree in computer science, machine learning, mathematics, or a related discipline
  • Experience deploying machine learning and data science solutions to production environments
  • Exposure to DevOps and cloud infrastructure (e.g., Docker, K8s, and CI/CD)
  • Experience processing unstructured data types (e.g., imagery, full-motion video, text, acoustic, sonar, RF, geospatial, graphs, telemetry signals
  • Experience building AI agents and agentic workflows
  • Experience implementing ETL pipelines, data pipelines, and/or workflow automation
  • Experience developing software in a compiled programming language (e.g., Go, Rust, C++, Java, etc.)
  • Experience building full-stack applications (i.e., back end, front end, REST)
  • Experience working with federal, state, and/or local government customers

This position offers a hybrid/on-site work environment at customer sites at Schofield Barracks in O฿ตahu, Hawai฿ตi. You will be expected to travel up to 30% of the time, including some international travel.
Compensation
The anticipated base pay range for this position is $220,000-$270,000/year. Striveworks' total compensation package includes a competitive base salary, equity grants, and cash bonuses.
Benefits include:
  • Medical/dental/vision insurance
  • Voluntary life, long-term disability, accident, and hospital indemnity insurance
  • HSA and FSA (including dependent care FSA) plans
  • 401(k) plan
  • Unlimited PTO
  • Paid parental leave

Ready to build systems that work for a mission that matters? Let's talk.
Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind.
If you require assistance or a reasonable accommodation in the application process, please contact People Operations at hr@striveworks.us.
In compliance with federal law, all persons hired will be required to verify their identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire.
Striveworks is a participating employer in the E-Verify program.

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