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Fraud Detection Machine Learning Jobs in Tennessee

Utilizes advanced machine learning and computer vision techniques to enhance production quality ... Develop algorithms for object detection, classification, and defect recognition. * Test and ...

Utilizes advanced machine learning and computer vision techniques to enhance production quality ... Develop algorithms for object detection, classification, and defect recognition. * Test and ...

... learning opportunities. - The Auditor will work under the direction of the client attorneys within ... The Auditor will perform audit activities related to the detection and investigation of fraud ...

Auditor

Knoxville, TN

$80K - $100K/yr

... learning opportunities. - The Auditor will work under the direction of the client attorneys within ... The Auditor will perform audit activities related to the detection and investigation of fraud ...

Junior AI Developer

Memphis, TN · On-site +1

$60K - $78K/yr

... machine learning, or backend development. General Skills: Must have strong software engineering ... detection, toxicity filters, and guardrails. Optimize performance and cost: batching, caching ...

Senior Data Engineer

Memphis, TN · On-site

$103K - $140K/yr

... produce machine learning-ready feature sets for model training and inference. • Enforce data ... detect schema drift, completeness gaps, and business-rule violations across pipeline stages. • ...

Senior Data Engineer

Memphis, TN · On-site

$95K - $129K/yr

Maintain Feature Store pipelines that produce machine learning-ready feature sets for model ... Build and maintain data quality validation scripts to detect schema drift, completeness gaps, and ...

Showing results 41-60

Fraud Detection Machine Learning information

See Tennessee salary details

$9

$16

$24

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

As of Jul 25, 2026, the average hourly pay for fraud detection machine learning in Tennessee is $16.38, according to ZipRecruiter salary data. Most workers in this role earn between $13.51 and $17.45 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 Tennessee? For Fraud Detection Machine Learning jobs in Tennessee, the most frequently searched job titles are:
What job categories do people searching Fraud Detection Machine Learning jobs in Tennessee look for? The top searched job categories for Fraud Detection Machine Learning jobs in Tennessee are:
What cities in Tennessee are hiring for Fraud Detection Machine Learning jobs? Cities in Tennessee with the most Fraud Detection Machine Learning job openings:
Process Engineer 3

Process Engineer 3

Denso

Maryville, TN

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 23 days ago


DENSO rating

7.5

Company rating: 7.5 out of 10

Based on 129 frontline employees who took The Breakroom Quiz

15th of 44 rated automakers


Job description

Job Summary:

Under limited supervision, designs, develops, and deploys AI-based vision systems to improve manufacturing and assembly processes across North America. Utilizes advanced machine learning and computer vision techniques to enhance production quality, robustness, and efficiency. Collaborates closely with a cross-functional Manufacturing affiliate network through the AI Vision Inspection Council, serving as a technical contributor and subject-matter expert to identify, test, validate, and standardize AI vision technologies. Supports capability development within Manufacturing affiliates through structured training, knowledge transfer, and implementation guidance. Self-starter capable of managing multiple initiatives with minimal direction while coordinating regionally aligned AI vision strategies.

Essential Duties and Responsibilities:

  1. System Development:
    1. Design, develop, and deploy AI-based vision systems for manufacturing and automation applications.
    2. Collaborate with mechanical, electrical, and software engineering teams to integrate vision systems into existing and new automation equipment.
    3. Support AI Vision Inspection Council activities by assessing technology readiness and applicability across NA Manufacturing environment.
  2. Implementation and Testing
    1. Develop algorithms for object detection, classification, and defect recognition.
    2. Test and validate AI vision systems in collaboration with Manufacturing affiliates to ensure accuracy, robustness, and production readiness.
    3. Support structured pilot deployments and document results to inform broader NA implementation decisions.
  3. Optimization and Sustainment
    1. Monitor deployed AI vision systems and support continuous performance optimization.
    2. Provide technical guidance for troubleshooting and long-term sustainment within Manufacturing affiliates.
    3. Support upgrades and evolution of vision systems as a part of standardized NA roadmaps.
  4. Road-mapping and Coordination
    1. Develop and manage AI vision implementation maps and roadmaps in coordination with the AI Vision Inspection Council.
    2. Align technical solutions with Manufacturing affiliate readiness, resources, and strategic priorities.
    3. Document standards, validation results, and deployment guidance for reuse across the NA region.
  5. Collaboration, Traning, and Knowledge Transfer
    1. Work closely with Automation, Quality, IT/Digital, and Manufacturing affiliate teams.
    2. Develop and deliver technical training materials, workshops, and on-the-job support for Manufacturing affiliate engineers.
    3. Enable Manufacturing affiliates to independently deploy, operate, and sustain AI vision inspection systems.

Minimum Level of Education and Training Required:

  • Requires a Bachelor's degree in Electrical or Mechanical engineering, Computer Science, Robotics, or related field and 3 or more years of relevant experience.
  • Proven experience in developing and deploying AI-based vision systems in an industrial or manufacturing setting.
  • Strong background in machine learning, computer vision, and image processing techniques.
  • Experience with machine vision hardware and software tools (e.g., cameras, lighting, VisionPro, OpenCV, TensorFlow, PyTorch).

Minimum Level of Knowledge and Skills Required:

  • Proficient in programming languages such as Python, C++, or similar.
  • Knowledge of deep learning frameworks and tools for vision applications.
  • Strong problem-solving skills and attention to detail.
  • Excellent project management and organizational skills.
  • Effective communication and teamwork abilities.

Preferred Qualifications:

  • Experience with industrial automation and robotics
  • Familiarity with real-time operating systems and embedded systems
  • Knowledge of production processes and quality control methodologies
  • Experience supporting cross-functional governance bodies, councils, or communities of practice within a manufacturing or automation environment.

Physical Requirements and Work Environment:

Visual requirements include color, depth perception and field of vision.  Physical requirements include standing, walking, pushing, pulling, lifting, talking, hearing and repetitive motions.  Position work environment is typically indoors in pleasant, well-lighted area with comfortable temperatures and in a controlled environment where no significant amounts of dust, fumes or odors.  Unavoidable accidents and health hazards are unlikely.  

Benefits Summary:

  • Medical, Dental, Vision, Prescription Drug Plans
  • 401K with 4% Company Match 
  • Vacation/PTO and 13 Paid Holidays
  • Bonus Program 
  • FSA/HSA and Dependent Care Programs
  • Company provided Life, Disability, ADD, and Business Travel Insurance
  • Various No Cost Wellness & Chronic Condition Management Programs
  • Various Optional Insurance Programs such as Legal, Identity Theft, Critical Illness, etc. 
  • Tuition Reimbursement 
  • Career Development and Ongoing Training 
  • Employee Assistance Program 
  • Employee Spotlight and Recognition Program
  • Volunteer opportunities 
  • Onsite Fitness Center (vary by location)
  • Cafeteria and food markets (vary by location)
  • Onsite Health Clinic and Pharmacy (vary by location) 

Candidates residing 50+ miles from the work location are eligible for relocation assistance. 

Annual Salary: $96,400 - $120,400
 


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