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Fraud Detection Supervisor Jobs (NOW HIRING)

Velera

Bilingual Spanish Fraud Detection Rep- REMOTE

$15.75 - $20/hr

Supervisory Responsibility * None Work at Home Technology Requirements * A secure home office ... Fraud Detection case processing application * Main queue collection * Starstation * 3270

Fifth Third

$60 - $80/hr

Fraud Detection - Responsible for analyzing and decisioning alerts on fraud detection systems to ... SUPERVISORY RESPONSIBILITIES None. MINIMUM KNOWLEDGE, SKILLS & ABILITIES REQUIRED One to three ...

Origin Bank

Fraud Analyst

Ruston, LA · On-site

Review and process mobile deposits daily to detect and prevent fraud while also ensuring ... Supervisory Responsibilities This job has no supervisory responsibilities. Qualifications To ...

Origin Bank

Fraud Analyst

Ruston, LA

Review and process mobile deposits daily to detect and prevent fraud while also ensuring ... Supervisory Responsibilities This job has no supervisory responsibilities. Qualifications To ...

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Fraud Detection Supervisor information

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$29.5K

$63.8K

$109.5K

How much do fraud detection supervisor jobs pay per year?

As of Sep 9, 2026, the average yearly pay for fraud detection supervisor in the United States is $63,834.00, according to ZipRecruiter salary data. Most workers in this role earn between $48,000.00 and $75,000.00 per year, depending on experience, location, and employer.

What does a fraud detection supervisor do?

A Fraud Detection Supervisor oversees a team responsible for identifying and preventing fraudulent activities within an organization. They analyze reports, monitor transactions, and ensure that fraud detection procedures are followed correctly. Supervisors also train staff, implement new strategies to reduce fraud, and collaborate with other departments to investigate suspicious behavior. Their role is crucial in maintaining the integrity and security of financial or sensitive data for the company.

What are the key skills and qualifications needed to thrive as a fraud detection supervisor, and why are they important?

To thrive as a Fraud Detection Supervisor, you need expertise in fraud analysis, risk management, and investigative techniques, typically backed by a bachelor's degree in finance, criminal justice, or a related field. Familiarity with fraud detection software, data analytics tools, and case management systems is often required, along with certifications like CFE (Certified Fraud Examiner). Strong leadership, attention to detail, and effective communication are essential soft skills for guiding teams and coordinating with other departments. These skills are crucial to ensuring accurate detection, swift response to fraudulent activities, and maintaining organizational integrity.

What are some common challenges faced by a fraud detection supervisor, and how can they be addressed?

A Fraud Detection Supervisor often encounters challenges such as rapidly evolving fraud tactics, balancing workload among team members, and ensuring compliance with regulatory requirements. Staying updated on the latest fraud trends and leveraging advanced detection technologies can help address these issues. Additionally, fostering clear communication within the team and providing ongoing training helps maintain high performance and adaptability. Supervisors also need to coordinate closely with other departments, such as risk management and IT, to effectively mitigate threats.

What is the difference between Fraud Detection Supervisor vs Fraud Analyst?

AspectFraud Detection SupervisorFraud Analyst
CredentialsTypically requires a bachelor’s degree in finance, criminal justice, or related field; certifications like CFE or ACFE are commonSimilar credentials; often holds a bachelor’s degree and may pursue certifications like CFE
Work EnvironmentSupervises teams in financial institutions, insurance companies, or e-commerce firmsAnalyzes transactions and patterns within similar environments
Employer & Industry UsageUsed in banking, finance, insurance, and retail sectorsCommonly employed in the same industries for detecting fraud patterns

While both roles focus on preventing fraud, the Fraud Detection Supervisor oversees teams and manages fraud prevention strategies, whereas the Fraud Analyst conducts detailed investigations and analyzes data to identify fraudulent activity.

What cities are hiring for Fraud Detection Supervisor jobs?

Cities with the most Fraud Detection Supervisor job openings:

What states have the most Fraud Detection Supervisor jobs?

States with the most job openings for Fraud Detection Supervisor jobs include:

What are popular job titles related to Fraud Detection Supervisor jobs?

For Fraud Detection Supervisor jobs, the most frequently searched job titles are:

Fraud Detection Supervisor jobs near you

Data Scientist - Fraud Detection

Mountain View, CA • On-site

DataVisor
Software Development • 1 - 10 employees
Learn more about DataVisorexternal

Full-time

Medical, PTO

Posted 14 days ago

Job description

About DataVisor:
DataVisor is the world's leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy consolidation and enrichment of any data, DataVisor's fraud and anti-money laundering (AML) solutions scale infinitely and enable organizations to act on fast-evolving fraud and money laundering activities in real time. Its patented unsupervised machine learning technology, advanced device intelligence, powerful decision engine, and investigation tools work together to provide significant performance lift from day one. DataVisor's platform is architected to support multiple use cases across different business units flexibly, dramatically lowering total cost of ownership, compared to legacy point solutions. DataVisor is recognized as an industry leader and has been adopted by many Fortune 500 companies across the globe.
Our award-winning software platform is powered by a team of world-class experts in big data, machine learning, security, and scalable infrastructure. Our culture is open, positive, collaborative, and results-driven. Come join us!
Position Overview:
We are looking for a motivated Entry-Level Data Scientist to join our Fraud Detection team. In this role, you will leverage your machine learning and data analysis skills to identify fraudulent activities, build predictive models, and uncover hidden patterns in large datasets. You will work closely with cross-functional teams to develop scalable solutions that enhance our fraud detection capabilities. This is a great opportunity to grow your skills in a fast-paced, data-driven environment while making a real impact in the fight against fraud.
Key Responsibilities:
  • Develop and deploy machine learning models for fraud detection and risk assessment.
  • Perform exploratory data analysis (EDA) to identify trends, anomalies, and patterns in transactional data.
  • Clean, preprocess, and analyze large datasets using Python and popular data science libraries (pandas, NumPy, scikit-learn, etc.).
  • Collaborate with engineering and business teams to integrate ML models into production systems.
  • Continuously monitor model performance and refine algorithms to improve accuracy.
  • Stay updated with the latest advancements in fraud detection techniques and ML/AI technologies.

Requirements
  • Master's degree in Computer Science, Data Science, Statistics, or a related quantitative field. Ph.D. degree is a plus.
  • Strong programming skills in Python and familiarity with data science libraries (NumPy, Pandas, scikit-learn, TensorFlow/PyTorch is a plus).
  • Solid understanding of machine learning algorithms (supervised/unsupervised learning, anomaly detection, classification, etc.).
  • Experience with SQL and data manipulation/analysis in large datasets.
  • Strong problem-solving skills and patience for deep-dive data exploration.
  • Prior internship or project experience in fraud modeling, risk analysis, or related fields is a plus.
  • Excellent communication skills and ability to work in a collaborative environment.

Nice to have
  • Familiarity with big data tools (Spark, Hadoop, Dask).
  • Knowledge of graph-based fraud detection techniques.
  • Experience with cloud platforms (AWS, GCP, Azure).

Benefits
PTO, Stock Option, Health Benefits

Apply