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Fraud Analytics Jobs in Minnesota (NOW HIRING)

Leverage approved AI, analytics, automation, and visualization tools to accelerate insight generation, improve operational efficiency, and enhance fraud detection capabilities * Collaborate closely ...

Leverage approved AI, analytics, automation, and visualization tools to accelerate insight generation, improve operational efficiency, and enhance fraud detection capabilities * Collaborate closely ...

Fraud Analyst

Oakdale, MN · Hybrid

$65K - $75K/yr

Osaic Careers Anit-Money Laundering Opportunity in Financial Services Fraud Analyst Location(s): Atlanta: 2300 Windy Ridge Pkwy SE, Suite750, Atlanta, GA 30339 La Vista:12325 Port Grace Blvd, La ...

Monitor and analyze identity theft fraud patterns to identify emerging fraud risks in both new applications and account takeover. * Develop and execute strategic initiatives to address ID Theft fraud ...

Monitor and analyze identity theft fraud patterns to identify emerging fraud risks in both new applications and account takeover. * Develop and execute strategic initiatives to address ID Theft fraud ...

This role combines advanced analytics, strategic problem-solving, and cross-functional collaboration to identify emerging fraud risks, uncover root causes, and support proactive loss mitigation. The ...

This role combines advanced analytics, strategic problem-solving, and cross-functional collaboration to identify emerging fraud risks, uncover root causes, and support proactive loss mitigation. The ...

The Fraud Analyst II is a valued part of a cohesive team focused on protecting the assets of the bank and its customers. Reviewing transactions for possible fraud and suspicious activity.

Fraud Analyst II

Minnetonka, MN · On-site

$22 - $30/hr

The Fraud Analyst II is a valued part of a cohesive team focused on protecting the assets of the bank and its customers. Reviewing transactions for possible fraud and suspicious activity.

Fraud Analyst II

Saint Paul, MN · On-site

$22 - $30/hr

The Fraud Analyst II is a valued part of a cohesive team focused on protecting the assets of the bank and its customers. Reviewing transactions for possible fraud and suspicious activity.

Fraud Analyst II

Eagan, MN · On-site

$22 - $30/hr

The Fraud Analyst II is a valued part of a cohesive team focused on protecting the assets of the bank and its customers. Reviewing transactions for possible fraud and suspicious activity.

... Fraud analytics experience is a plus. Company : RELX is a provider of information-based analytics for professional and business customs. Founded in 1993, the company is headquartered in London, GBR ...

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Fraud Analytics information

See Minnesota salary details

$15

$30

$62

How much do fraud analytics jobs pay per hour?

As of Aug 26, 2026, the average hourly pay for fraud analytics in Minnesota is $30.05, according to ZipRecruiter salary data. Most workers in this role earn between $20.72 and $33.17 per hour, depending on experience, location, and employer.

What is fraud analytics?

Fraud analytics is the process of using data analysis, statistical methods, and machine learning techniques to detect, prevent, and investigate fraudulent activities within an organization. Professionals in this field analyze large sets of transactional and behavioral data to identify patterns and anomalies that may indicate fraud. Fraud analytics is commonly used in industries such as banking, insurance, retail, and e-commerce to minimize financial losses and protect customers. The role often involves working with specialized software and collaborating with other teams to implement effective anti-fraud strategies.

How does a fraud analytics professional typically collaborate with other departments within an organization?

Fraud Analytics professionals frequently work cross-functionally, partnering with teams such as IT, compliance, risk management, and customer service. They analyze data to identify suspicious activities and then communicate findings to relevant stakeholders, often participating in investigations or recommending process improvements. Effective collaboration ensures that fraud detection strategies stay up-to-date and align with broader organizational goals, making strong communication skills and teamwork essential for success in this role.

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

To thrive in Fraud Analytics, you need strong analytical abilities, proficiency in statistics, and experience with data analysis, often supported by a degree in mathematics, statistics, computer science, or a related field. Familiarity with data mining tools, SQL, Python, machine learning platforms, and certifications like Certified Fraud Examiner (CFE) are typically required. Attention to detail, critical thinking, and effective communication are essential soft skills for interpreting data patterns and presenting findings to stakeholders. These skills are crucial for detecting fraudulent activities, minimizing financial risks, and supporting organizational integrity.

What is the difference between Fraud Analytics vs Fraud Prevention Specialist?

AspectFraud AnalyticsFraud Prevention Specialist
Primary FocusAnalyzing data to detect and predict fraudulent activitiesImplementing strategies and actions to prevent fraud
Skills & CertificationsData analysis, statistical tools, SQL, certifications like Certified Fraud Examiner (CFE)Customer service, risk management, fraud detection techniques, certifications like CFE
Work EnvironmentData analysis teams, financial institutions, tech companiesCustomer support centers, financial institutions, retail
GoalsIdentify patterns, develop models, improve detection accuracyReduce fraud incidents, enhance prevention measures

While both roles aim to combat fraud, Fraud Analytics focuses on analyzing data to identify and predict fraudulent activities, whereas Fraud Prevention Specialists implement measures to prevent fraud from occurring. Both roles often collaborate but serve different functions within fraud management strategies.

How do I become a fraud analyst?

To become a fraud analyst, typically a bachelor's degree in finance, accounting, or a related field is required. Relevant skills include data analysis, knowledge of fraud detection tools, and familiarity with databases and reporting software; certifications like Certified Fraud Examiner (CFE) can enhance prospects. Gaining experience through internships or entry-level roles in finance or security is also beneficial.

How much does a fraud analyst get paid?

A fraud analyst's salary typically ranges from $50,000 to $80,000 annually, depending on experience, location, and industry. Entry-level positions may start lower, while experienced analysts with certifications or specialized skills can earn higher salaries. Many roles also include benefits such as bonuses and professional development opportunities.

Is fraud analysis a good career?

Fraud analysis is a growing field within risk management that involves detecting and preventing fraudulent activities using data analysis and investigative skills. It offers opportunities for advancement, requires knowledge of analytics tools, and often involves working in financial or e-commerce environments. The role can be stable and rewarding for those interested in security and data-driven decision making.

What does a fraud analytics do?

A fraud analyst uses data analysis techniques to detect and prevent fraudulent activities within financial transactions or business operations. They analyze large datasets, identify patterns of suspicious behavior, and implement strategies to reduce fraud risk, often using tools like SQL, Excel, or specialized fraud detection software. Strong analytical skills and knowledge of fraud schemes are essential for this role.

What are the most commonly searched types of Fraud Analytics jobs in Minnesota?

The most popular types of Fraud Analytics jobs in Minnesota are:

What are popular job titles related to Fraud Analytics jobs in Minnesota?

For Fraud Analytics jobs in Minnesota, the most frequently searched job titles are:

What job categories do people searching Fraud Analytics jobs in Minnesota look for?

The top searched job categories for Fraud Analytics jobs in Minnesota are:

Infographic showing various Fraud Analytics job openings in Minnesota as of August 2026, with employment types broken down into 1% Internship, 91% Full Time, 2% Part Time, and 6% Contract. Highlights an 77% Physical, 7% Hybrid, and 16% Remote job distribution, with an average salary of $62,508 per year, or $30.1 per hour.

Senior Fraud Data Analyst - Commercial Fraud Operations Analytics Lead - Remote

UnitedHealth Group

Eden Prairie, MN • On-site, Remote

Full-time

Retirement

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


UnitedHealth Group rating

7.6

Company rating: 7.6 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

191st of 893 rated healthcare providers


Job description

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health optimization on a global scale. Join us to start Caring. Connecting. Growing together.


Optum Financial prevents and responds to fraud to protect customers and the business. The Senior Fraud Data Analyst serves as the analytics workstream lead for Commercial Fraud Operations, supporting the Commercial Payments line of business. This role leverages advanced analytics, machine learning, and AI-enabled insights to support fraud monitoring, investigations, risk decisioning, and loss mitigation across Commercial Payments products and channels. In partnership with Commercial Fraud Operations, Product, Technology, and Risk stakeholders, the individual will define requirements, build scalable reporting and analytics solutions, evaluate fraud detection performance, and identify opportunities to improve operational effectiveness and fraud outcomes. "Lead" reflects ownership of analytics delivery, stakeholder alignment, and prioritization of workstreams rather than direct people management.


You'll enjoy the flexibility to work remotely * from anywhere within the U.S. as you take on some tough challenges. For all hires in the Minneapolis or Washington, D.C. area, you will be required to work in the office a minimum of four days per week.


Primary Responsibilities:

  • Fraud Analytics Strategy & Delivery (Workstream Lead)
    • Lead intake, prioritization, sequencing, and delivery coordination for fraud analytics initiatives supporting Commercial Payments, managing multiple concurrent stakeholder requests and dependencies
    • Translate business objectives into measurable analytics deliverables, ensuring timely execution and adoption of solutions
    • Define business requirements and delivery priorities for scalable fraud analytics capabilities, partnering with Product, Technology, Data Science, and Fraud Operations stakeholders to deliver actionable fraud intelligence, performance insights, risk monitoring, and decision support across Commercial Payments
  • AI-Driven Fraud Detection & Optimization
    • Partner with Commercial Fraud Operations, Product, and Technology teams to develop, evaluate, and optimize fraud detection strategies utilizing rules, predictive analytics, machine learning models, and AI-enabled monitoring capabilities
    • Evaluate model and rule performance using key measures such as precision, recall, false positive rates, fraud capture rates, and operational impact
  • Data Analytics, Insights & Risk Mitigation
    • Analyze large, complex datasets containing transaction, fraud case, operational, and customer data to identify emerging fraud trends, root causes, and control opportunities
    • Deliver actionable recommendations that reduce fraud losses, improve operational efficiency, and strengthen risk controls
    • Define requirements and support development of a commercial payments fraud intelligence repository or data product that consolidates information from multiple sources to build fraud profiles, identify emerging threats, and support fraud detection, prevention, investigation, reporting, and risk mitigation activities
  • Performance Reporting & Executive Storytelling
    • Design and maintain enterprise dashboards and reporting solutions using tools such as Power BI or Tableau
    • Communicate analytics findings and business implications through executive-ready presentations, supporting operational, product, and risk management decisions
  • Analytics Automation & AI Enablement
    • Support basic data architecture and engineering needs by building foundational reports, datasets, and pipelines that convert bronze medallion tables to silver and gold, creating the infrastructure needed for scalable reporting, dashboards, and advanced analytics
    • Develop and maintain automated analytics workflows using SQL, Python, AI-assisted analytics tools, or related technologies to improve reporting scalability and efficiency, including use of generative AI tools to write, review, and debug code where appropriate
    • Identify opportunities to leverage generative AI and advanced analytics capabilities to enhance fraud investigations, monitoring, and operational decision-making
  • Governance, Metrics & Documentation
    • Navigate complex organizational processes to obtain approvals for data access, usage, and governance initiatives
    • Establish and maintain standardized KPI definitions, metric libraries, data quality controls, and governance documentation
    • Ensure fraud analytics outputs are reproducible, audit-ready, and aligned with enterprise governance standards


You'll be rewarded and recognized for your performance in an environment that will challenge you and give you clear direction on what it takes to succeed in your role as well as provide development for other roles you may be interested in.

Required Qualifications:

  • 5 years of experience in fraud analytics, risk analytics, financial crime, payments analytics, business intelligence, or a related analytical function
  • 5 years of SQL with experience querying and analyzing large-scale datasets containing millions of records
  • 3 years of experience with analytics initiatives or cross-functional workstreams, including stakeholder management, prioritization, and delivery accountability
  • 2 years of experience developing analytics solutions using Python, R, SAS, or similar programming languages, with hands-on experience leveraging cloud-based analytics platforms such as MS Fabric, Databricks, Snowflake, Google Cloud Platform or Amazon RedShift
  • 2 years of experience building dashboards and reporting solutions using Power BI, Tableau, or comparable visualization platforms
  • Demonstrated experience applying statistical analysis, predictive modeling, machine learning, AI-enabled analytics, or anomaly detection techniques to solve business problems
  • Experience defining, monitoring, and improving operational KPIs, controls, and performance metrics
  • Experience translating analytical findings into operational recommendations, fraud detection improvements, control enhancements, or measurable risk reduction outcomes
  • Experience managing end-to-end analytics delivery, including requirements gathering, data validation, testing, implementation, and post-production monitoring


Preferred Qualifications:

  • Professional certifications such as Certified Fraud Examiner (CFE), Certified Analytics Professional (CAP), Certified Financial Crime Specialist (CFCS), Azure Data Scientist Associate, Databricks certifications, or comparable analytics, fraud, or AI credentials
  • Experience partnering with Product, Engineering, and Data Science teams to deploy fraud analytics, machine learning models, or AI-enabled capabilities into production environments
  • Experience using generative AI tools to support coding activities, including drafting, reviewing, debugging, or improving SQL, Python, or related analytics code
  • Experience optimizing fraud detection strategy through rule mining, champion/challenger testing, segmentation analysis, and other optimization methodologies
  • Experience with generative AI, machine learning, natural language processing (NLP), or AI-assisted investigation tools in a fraud, risk, or operations environment
  • Experience supporting regulatory, audit, compliance, or risk governance reviews within a highly regulated industry
  • Experience with Commercial Payments products, including ACH, wire transfers, virtual cards, checks, and emerging payment channels
  • Demonstrated ability to operate effectively in ambiguous environments, establish structure where processes, reporting, or analytics capabilities do not yet exist, and influence stakeholders across operations, product, technology, and risk functions


*All employees working remotely will be required to adhere to UnitedHealth Group's Telecommuter Policy


Pay is based on several factors including but not limited to local labor markets, education, work experience, certifications, etc. In addition to your salary, we offer benefits such as, a comprehensive benefits package, incentive and recognition programs, equity stock purchase and 401k contribution (all benefits are subject to eligibility requirements). No matter where or when you begin a career with us, you'll find a far-reaching choice of benefits and incentives. The salary for this role will range from $91,700 - $163,700 annually based on full-time employment. We comply with all minimum wage laws as applicable.


Application Deadline: This will be posted for a minimum of 2 business days or until a sufficient candidate pool has been collected. Job posting may come down early due to volume of applicants.


At UnitedHealth Group, our mission is to help people live healthier lives and make the health system work better for everyone. We believe everyone-of every race, gender, sexuality, age, location and income-deserves the opportunity to live their healthiest life. Today, however, there are still far too many barriers to good health which are disproportionately experienced by people of color, historically marginalized groups and those with lower incomes. We are committed to mitigating our impact on the environment and enabling and delivering equitable care that addresses health disparities and improves health outcomes - an enterprise priority reflected in our mission.

UnitedHealth Group is an Equal Employment Opportunity employer under applicable law and qualified applicants will receive consideration for employment without regard to race, national origin, religion, age, color, sex, sexual orientation, gender identity, disability, or protected veteran status, or any other characteristic protected by local, state, or federal laws, rules, or regulations.


UnitedHealth Group is a drug-free workplace. Candidates are required to pass a drug test before beginning employment.


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