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Fraud Detection Machine Learning Jobs in Tomball, TX

Senior Security Engineer

Houston, TX · On-site

$109K - $149K/yr

Hands-on experience with AI, machine learning, security analytics, or advanced detection capabilities. * Experience implementing security automation, orchestration, and API integrations. * Knowledge ...

AI Engineer III

Houston, TX · On-site

$124 - $132/hr

Design, develop, and deploy scalable machine learning models (predictive, classification, anomaly detection, clustering) and AI-powered solutions such as intelligent assistants, forecasting systems ...

Design, develop, and deploy scalable machine learning models (predictive, classification, anomaly detection, clustering) and AI-powered solutions such as intelligent assistants, forecasting systems ...

AI Engineer III

Houston, TX · On-site

$124K - $132K/yr

Design, develop, and deploy scalable machine learning models (predictive, classification, anomaly detection, clustering) and AI-powered solutions such as intelligent assistants, forecasting systems ...

Showing results 21-40

Fraud Detection Machine Learning information

See Tomball, TX salary details

$10

$17

$25

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

As of Sep 3, 2026, the average hourly pay for fraud detection machine learning in Tomball, TX is $17.09, according to ZipRecruiter salary data. Most workers in this role earn between $14.09 and $18.22 per hour, depending on experience, location, and employer.

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 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 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 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 popular job titles related to Fraud Detection Machine Learning jobs in Tomball, TX?

For Fraud Detection Machine Learning jobs in Tomball, TX, the most frequently searched job titles are:

Sr. Delivery Consultant - AI/ML, AWSI Energy SDT

Amazon

Houston, TX

Full-time

Posted 14 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,146 frontline employees who took The Breakroom Quiz

5th of 39 rated national retailers


Job description

Join AWS Professional Services' Energy segment in Houston as a Data Scientist and help global enterprises turn complex data into real business impact with AI. You'll design, build, validate, and deploy end-to-end machine learning and deep learning solutions on AWS-working alongside Big Data and DevOps specialists to take models from discovery through production.
This is an opportunity to solve high-value customer problems using AWS AI services, modern ML/DL frameworks, and large-scale cloud infrastructure, while exploring emerging approaches in areas such as model monitoring and retraining. If you are curious, customer-focused, love diving deep into data, and want to grow with a collaborative team at the forefront of cloud AI, this role offers meaningful technical challenges, mentorship, and strong career development opportunities in a high-growth industry segment for AWS cloud.
Key job responsibilities
As an experienced Professional Services Sales Leader, you will be responsible for:
Leading and developing a high-performing team of Account Executives and Cloud Architects
Developing and supporting execution of sales strategies to meet team targets and drive revenue growth
Managing customer relationships, ensuring high satisfaction and identifying new opportunities
Leveraging deep AWS knowledge to guide sellers in proposing optimal solutions
Monitoring and analyzing key performance indicators, ensuring accurate reporting and forecasting to optimize operational processes and manage risk
A day in the life
As an AWS Professional Services Data Scientist, you will partner with enterprise and public-sector customers to identify high-value AI/ML opportunities and translate business challenges into scalable cloud solutions

Day to day, you will work with customer business leaders, data teams, IT teams, and product owners to assess data, build and validate ML/DL models, and communicate results. You will collaborate with AWS consultants from other specialty disciplines to deploy, monitor, and retrain models. Typical problems include forecasting, fraud or anomaly detection, personalization, document automation, and operational optimization.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Amazon logo

About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US