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Fraud Detection Machine Learning Jobs in Cincinnati, OH

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

Fraud Risk Analytics Manager

Mason, OH · Hybrid

$106K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Strong experience with fraud detection, prevention, and decisioning systems in complex environments ... Solid foundation in data science and statistical learning , including: * Classification and ...

Fraud Risk Analytics Manager

Mason, OH · Hybrid

$106K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Strong experience with fraud detection, prevention, and decisioning systems in complex environments ... Solid foundation in data science and statistical learning , including: * Classification and ...

Fraud Risk Analytics Manager

Mason, OH · Hybrid

$106K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Strong experience with fraud detection, prevention, and decisioning systems in complex environments ... Solid foundation in data science and statistical learning , including: * Classification and ...

Fraud Risk Analytics Manager

Mason, OH · Hybrid

$106K - $130K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Strong experience with fraud detection, prevention, and decisioning systems in complex environments ... Solid foundation in data science and statistical learning , including: * Classification and ...

Senior Data Scientist (SMTS)

Bellevue, KY · On-site

$148.50 - $223.90/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

... machine learning.*** **You partner with threat experts to understand evolving threat patterns and their detection. You collaborate effectively with software engineers to champion proven detection ...

AI Engineering Intern - Fall 2026

Cincinnati, OH · On-site +1

$16 - $21/hr

  • Medical

  • Retirement

  • PTO

Research, develop, and implement machine learning algorithms and models for tasks such as classification, regression, clustering, anomaly detection, and recommendation systems; * Research, develop ...

AI Engineering Intern - Fall 2026

Cincinnati, OH · On-site

$16 - $21/hr

  • Medical

  • Retirement

  • PTO

Research, develop, and implement machine learning algorithms and models for tasks such as classification, regression, clustering, anomaly detection, and recommendation systems; * Research, develop ...

Develop supervised and unsupervised machine learning solutions, including classification, regression, clustering, forecasting, recommendation, anomaly detection, optimization, and related techniques.

... and Machine Learning solutions across various domains. The role involves collaborating with ... drift detection, and performance monitoring. • Establish model versioning, governance, and ...

Senior AI Engineer - SFL Scientific

Cincinnati, OH · On-site

$100K - $137K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... Some of our novel use cases include cancer detection, drug discovery, optimizing population health ...

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Fraud Detection Machine Learning information

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

As of Aug 15, 2026, the average hourly pay for fraud detection machine learning in Cincinnati, OH is $17.32, according to ZipRecruiter salary data. Most workers in this role earn between $14.28 and $18.46 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 Cincinnati, OH?

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

What job categories do people searching Fraud Detection Machine Learning jobs in Cincinnati, OH look for?

The top searched job categories for Fraud Detection Machine Learning jobs in Cincinnati, OH are:

What cities near Cincinnati, OH are hiring for Fraud Detection Machine Learning jobs?

Cities near Cincinnati, OH with the most Fraud Detection Machine Learning job openings:

Senior Manager Digital, Scam & Mule Fraud

Citizens Financial Group

Mason, OH • On-site, Remote

$148K - $180K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Description

The Senior Manager Digital, Scam & Mule Fraud leads enterprise strategy and execution to prevent, detect, and disrupt digital fraud, scam victimization, and money mule activity across customer channels. This role integrates fraud strategy, financial crime intelligence, customer protection, and operational response to reduce losses, protect customers, and strengthen regulatory compliance.

  • Combines fraud prevention with scam ecosystem defense.
  • Serves as a bridge between fraud, cyber, and product teams.
  • Focuses on proactive risk reduction rather than only reactive response.
Key Responsibilities
  • Risk Strategy & Oversight
    • Develop and execute a holistic digital fraud, money mule, and scam prevention strategy across channels, including online banking, payments, onboarding, and authentication.
    • Embed prevention-first controls across the product lifecycle and customer journeys.
    • Advise executive leadership on emerging fraud threats, regulatory expectations, and risk posture.
    • Define risk appetite, key performance indicators, and loss targets for digital fraud and scam exposure.
  • Analytical Leadership
    • Build and mentor a team of data scientists and analysts to develop and implement advanced machine learning and statistical models for fraud detection and prevention.
    • Drive portfolio fraud analytics across customer segments and provide actionable insights to inform risk strategies.
    • Develop predictive models to monitor and mitigate emerging fraud threats, integrating real-time detection capabilities with engineering and technology teams.
    • Use data-driven insights to recommend improvements to fraud prevention systems and technologies.
  • Program Development & Collaboration
    • Partner with internal stakeholders, external vendors, and customers to launch and update risk controls across products.
    • Act as Business Segment Relationship Manager for vendor partnerships, ensuring compliance with third-party risk management requirements.
    • Collaborate with audit, business segment, and corporate risk teams to address issues and support strategic objectives.
  • Operational Excellence
    • Manage, mentor, and develop a team within Fraud Strategy and Analytics, fostering a collaborative, innovative, and high-performance culture.
    • Establish team goals, measure performance, and ensure alignment with company objectives.
    • Drive operational efficiency and scale through process improvement, automation, and staff development.
    • Develop chargeback management strategies for card issuing and travel-related businesses.
  • Documentation & Compliance
    • Create and approve risk assessments for new product launches and enhancements.
    • Maintain current documentation, including credit policies, procedures, and process flows.
    • Ensure adherence to corporate and business unit policies, standards, and regulatory requirements.
Qualifications
  • Bachelor's degree required; advanced degree preferred. In lieu of a degree, additional years of segment-specific or risk-related experience may be considered.
  • 10+ years of experience in fraud strategy, fraud prevention, data analytics, and risk management.
  • 5+ years of experience in digital fraud risk management.
  • Deep expertise in identity and payment fraud methods, tools, and processes for prevention, detection, and fraud operations.
  • Advanced proficiency in data science techniques, including machine learning, predictive modeling, statistical analysis, and data.
  • Experience with fraud detection platforms, rule engines, and data visualization tools.
  • Strong understanding of payment processing systems, card networks, and risks specific to card transactions and corporate expense management.
  • Excellent analytical, organizational, and problem-solving skills.
  • Strong verbal and written communication skills, with the ability to present requirements and issues clearly.
  • Ability to lead multiple projects simultaneously, prioritize effectively, and thrive in a fast-paced, evolving environment.
  • Proficiency in Microsoft Office and analytical tools such as SageMaker, Python, R, SQL, and/or SAS.
  • Knowledge of risk management principles and regulatory compliance requirements.

Hours & Work Schedule

  • Hours per Week: 40
  • Work Schedule: Monday - Friday

Pay Transparency 

The salary range for this position is $148,000 - $180,000 per year plus an opportunity to earn an annual discretionary bonus. Actual pay is based on various factors including but not limited to the budget, work location, and relevant skills and experience. We offer competitive pay, comprehensive medical, dental and vision coverage, retirement benefits, maternity/paternity leave, flexible work arrangements, education reimbursement, wellness programs and more. Note, Citizens' paid time off policy exceeds the mandatory, paid sick or paid time-away policy of every local and state jurisdiction in the United States. For an overview of our benefits, visit https://jobs.citizensbank.com/benefits 

This role is not eligible for new employersponsored or current H-1 B visa holders. Applicants, including current OPT, L and other visa holders, must be authorized to work in the U.S. without the need for new employer sponsorship for themselves or their spouses now and in the future.

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Some job boards have started using jobseeker-reported data to estimate salary ranges for roles. If you apply and qualify for this role, a recruiter will discuss accurate pay guidance.

Equal Employment Opportunity

Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague's or a dependent's reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability.

Education:Why Work for UsEmployment Type: 1ST