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Fraud Detection Machine Learning Jobs in Tennessee

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics. * Curriculum Awareness & Adaptive Instruction:

Fraud Detection: Investigate flagged orders by analyzing account details and verifying information ... fax machines. This role occasionally must lift and carry office equipment. Occasional evening ...

... Machine Learning,Data Science, Data Engineering and Software Engineering. Position Overview ... Implement AI-driven data validation, schema drift detection, and metadata management. * Establish ...

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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 Jun 6, 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:
Fraud & Compliance Operations Director

Fraud & Compliance Operations Director

Avispa Technology

Nashville, TN โ€ข On-site

$60/hr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 3 days ago


Job description

Job Description
Fraud & Compliance Operations Director PMOUNTJP00001169
  • Hourly pay: $60/hr
  • Worksite: Leading digital streaming network (Nashville, TN 37201 - Onsite)
  • W2 Employment, Group Medical, Dental, Vision, Life, Retirement Savings Program, PSL
  • 40 hours/week, 6 Month Assignment

A leading digital streaming network seeks a Fraud & Compliance Operations Director to help build and operationalize a fraud and compliance monitoring program across corporate spend activities. This hands-on role will lead fraud detection, investigation, compliance monitoring, and reporting efforts across travel and entertainment expenses, corporate card programs, procure-to-pay workflows, and third-party vendor transactions while partnering closely with Finance, HR, Legal, Security, and Data Analytics teams.
Fraud & Compliance Operations Director Responsibilities:
  • Develop and help stand up fraud monitoring and compliance programs across corporate spend activities; create queries, monitoring cadences, and detection frameworks to identify irregularities, policy violations, noncompliance, and potential fraud across travel and entertainment, procure-to-pay, and vendor transactions.
  • Conduct end-to-end fraud investigations by analyzing expense reports, corporate card activity, business travel accounts, P-Card transactions, purchase orders, and supplier payments; validate findings, maintain audit documentation, and coordinate escalations with HR, Legal, Security, and other stakeholders.
  • Partner with Data Analytics teams to build and enhance fraud detection capabilities using data analysis, predictive modeling, monitoring tools, dashboards, and reporting frameworks that provide visibility into fraud trends, compliance risks, and operational performance.
  • Monitor compliance with expense reimbursement policies, financial controls, and PO governance processes; identify repeat violations, recommend corrective actions, support policy enforcement, and drive accountability across business functions.
  • Deliver actionable reporting and executive-level insights while collaborating with global stakeholders to strengthen controls, improve compliance processes, support awareness initiatives, and contribute both strategically and tactically within a rapidly evolving function.

Fraud & Compliance Operations Director Qualifications:
  • 5+ years of experience in fraud monitoring, fraud investigations, compliance operations, or related risk management functions.
  • Bachelor's degree in Accounting, Finance, Business Administration, or a related field.
  • Proven experience in detecting, evaluating, and investigating fraud within corporate expense, financial transaction, procurement, or vendor payment environments.
  • Strong data analytics skills with proficiency in SQL, Excel, and/or data visualization tools such as Power BI or Tableau.
  • Experience with financial systems such as Concur, SAP, or Oracle.
  • Experience developing queries, monitoring programs, and analytical frameworks used to identify fraud, policy violations, and compliance risks.
  • Understanding of expense reimbursement policies, internal controls, procure-to-pay processes, and purchase order compliance workflows.
  • Strong written and verbal communication skills with the ability to present findings and recommendations to stakeholders at all organizational levels.
  • Experience with machine learning or predictive modeling for fraud detection is preferred.
  • Certified Fraud Examiner (CFE), CPA, CIA, or similar certification is preferred.
  • Familiarity with SOX, AML, fraud detection technologies, and case management systems is preferred.
  • Experience within regulated industries such as financial services, banking, insurance, or similar environments is preferred.

Shift:
  • Monday-Friday, 8:00 AM-5:00 PM or 9:00 AM-6:00 PM.

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