1

Software Engineer Fraud Detection Jobs in Utah (NOW HIRING)

Develop and maintain an integrated fraud initiatives roadmap spanning prevention, detection ... engineering) and ensure rapid deployment of countermeasures. * Coordinate cross-functional ...

Senior Data Engineer

Provo, UT ยท On-site

$100K - $136K/yr

... fraud pipelines is strongly preferred. What You'll Do Design and build data pipelines. Develop ... Required Qualifications * 7+ years of professional experience as a Data Engineer or Software ...

About Netcraft Netcraft is the global leader in cybercrime detection and disruption. We're a ... The Role We're searching for a Backend Software Engineer to join our growing engineering team as ...

next page

Showing results 1-20

Software Engineer Fraud Detection information

What does a Software Engineer in Fraud Detection do?

A Software Engineer in Fraud Detection designs and develops systems to identify and prevent fraudulent activities within digital platforms, such as banking or e-commerce environments. They build algorithms to analyze user behavior, detect anomalies, and flag suspicious transactions in real time. Their work often involves machine learning, big data analysis, and close collaboration with data scientists and security teams to continuously improve fraud detection accuracy. These engineers play a key role in protecting businesses and customers from financial loss and cybercrime.

What is the difference between Software Engineer Fraud Detection vs Data Scientist Fraud Detection?

AspectSoftware Engineer Fraud DetectionData Scientist Fraud Detection
Required CredentialsBachelor's in CS or related field, programming skillsBachelor's or higher in CS, Statistics, or Data Science
Work EnvironmentDevelops fraud detection systems, writes code, implements algorithmsAnalyzes data, builds models, interprets results
Employer & Industry UsageFinancial institutions, fintech, e-commerceFinancial services, tech companies, insurance
Common Search & ComparisonFocuses on software development for fraud detectionFocuses on data analysis and modeling for fraud detection

While both roles work in fraud detection, Software Engineer Fraud Detection primarily develops and maintains detection systems through coding, whereas Data Scientist Fraud Detection analyzes data and builds models to identify fraudulent activity. Both roles often collaborate but differ in their core focus and skill sets.

What are the key skills and qualifications needed to thrive as a Software Engineer in Fraud Detection, and why are they important?

To thrive as a Software Engineer in Fraud Detection, strong programming skills (such as Python, Java, or Scala), a solid understanding of algorithms, data structures, and experience with machine learning or statistical analysis are generally required, often supported by a degree in computer science or a related field. Familiarity with big data platforms (like Hadoop or Spark), real-time analytics systems, and fraud detection tools or frameworks is typically expected. Analytical thinking, problem-solving abilities, and effective communication are key soft skills that differentiate top performers in this field. These skills are crucial for developing robust systems that can quickly identify and prevent fraudulent activities, protecting both users and organizations.

How does a Software Engineer in Fraud Detection typically collaborate with data scientists and analysts to identify fraudulent activity?

Software Engineers in Fraud Detection work closely with data scientists and analysts to build, refine, and deploy systems that detect and prevent fraud. While data scientists may develop models and identify patterns from large datasets, engineers are responsible for integrating these models into scalable, real-time systems within the company's technology stack. Regular communication and joint problem-solving are essential, as engineers must understand the logic behind models and analysts' findings to ensure accurate implementation and continuous improvement. This collaborative environment helps create robust fraud detection mechanisms that adapt to evolving threats.
What are popular job titles related to Software Engineer Fraud Detection jobs in Utah? For Software Engineer Fraud Detection jobs in Utah, the most frequently searched job titles are:
What job categories do people searching Software Engineer Fraud Detection jobs in Utah look for? The top searched job categories for Software Engineer Fraud Detection jobs in Utah are:
What cities in Utah are hiring for Software Engineer Fraud Detection jobs? Cities in Utah with the most Software Engineer Fraud Detection job openings:

Senior Fraud Operations Analyst

Mountain America Federal Credit Union

Sandy, UT โ€ข Hybrid

Full-time

Posted 7 days ago


Job description

Please reference the schedule and minimum qualifications listed below before applying.

If you need assistance with filling out our application form or during any phase of the application, interview, or employment process, please notify our Human Resources Team at 801-366-6947 option 1 or email macurecruiting@macu.com and every reasonable effort will be made to accommodate your needs in a timely manner.

Job SummaryThe Senior Fraud Operations Analyst monitors and responds to increasingly sophisticated suspicious activities across diverse transaction channels to safeguard member assets and uphold trust. The Analyst plays a critical role in safeguarding member assets by leading complex fraud investigations and driving strategic fraud prevention initiatives. This senior-level position involves analyzing high-risk referrals, adjusting account restrictions, conducting member outreach, and identifying fraud patterns across digital and physical channels. Investigators collaborate with cross-functional teams-including fraud analysts, engineers, and leadership-to reduce financial losses and enhance fraud detection systems. The role requires advanced analytical capabilities, fluency in fraud technologies, and a proactive mindset to anticipate emerging threats. Investigators also mentor junior team members and contribute to training, reporting, and system optimization efforts.Job Description
Job Description

LOCATION

Mountain America Center - Hybrid

9800 S Monroe St
Sandy, UT 84070

SCHEDULE

Full Time; this is a hybrid schedule- in office expectation will be based on business need.

To be effective, an individual must be able to perform each job duty successfully.

  • Utilize advanced fraud detection platforms-including AI-driven alert systems and behavioral analytics-to identify and investigate complex suspicious activities across digital and physical channels.
  • Analyze high-risk alerts and escalate cases involving potential fraud, account takeover, or synthetic identity threats.
  • Take decisive action in real-time to secure compromised accounts, prevent financial loss, and minimize disruption to legitimate member activity.
  • Thoroughly review affected accounts and adjust restrictions as needed based on review of alert activity.
  • Initiate outbound calls to members to determine fraud involvement, assess impact, and guide recovery efforts with empathy and professionalism.
  • Analyze fraud patterns, behavioral anomalies, and transaction trends to identify vulnerabilities and recommend rule enhancements.
  • Advocate for new fraud detection rules or system adjustments to close prevention gaps and improve alert accuracy.
  • Collaborate with fraud data analysts, engineers, and management to resolve financial loss cases and strengthen fraud infrastructure.
  • Collaborate with internal fraud strategy, cybersecurity, and data analytics teams to refine detection models and response protocols.
  • Partner with account investigators on complex or multi-channel fraud cases, including synthetic identity, mule activity, and account takeovers.
  • Represent the Alert Team in cross-functional meetings, sharing insights on fraud trends, system performance, and member impact.
  • Deliver onboarding and ongoing training to new hires and junior specialists, emphasizing fraud trends, system usage, and member empathy.
  • Document fraud incidents, resolution outcomes, and member impact in detailed reports for internal review and regulatory compliance.
  • Pull and interpret data from fraud platforms, biometric risk systems, and internal databases to support investigations and strategic planning.
  • Create detailed reports for leadership that highlight fraud exposures, operational risks, and opportunities for improvement.
  • Act as a junior data analyst by contributing to fraud model tuning, alert logic refinement, and predictive risk scoring.
  • Identify and communicate fraud trends, emerging attack vectors, and system vulnerabilities to data analysts and leadership.
  • Mentor Fraud Operations Analysts, as well as peers in Intake, Recovery, and Investigations teams, fostering a culture of excellence and continuous learning.
  • Serve as a point of escalation for member calls requiring advanced support or managerial intervention.
  • Lead training initiatives for support teams and branches, enhancing fraud awareness and updating internal knowledge resources.
  • Maintain expert-level knowledge of fraud detection systems, biometric risk tools, and digital identity verification technologies.
  • Advocate for system improvements and participate in vendor evaluations or pilot programs for new fraud tools.
  • Promptly log complaints and submit Suspicious Activity Reports (SARs) in accordance with regulatory requirements.
  • Ensure full compliance with applicable laws and regulations, including the Bank Secrecy Act, OFAC, FACT Act, GLBA, Regulation CC, Regulation DD, Regulation Z, Regulation E, and others relevant to fraud operations.
  • Uphold Mountain America's mission, vision, and values by delivering exceptional service and proactive fraud resolution to protect members' financial well-being.
  • Perform other duties as assigned.

KNOWLEDGE, SKILLS, and ABILITIES

The requirements listed are representative of the knowledge, skills, and/or abilities required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential job functions.

Experience

  • 3+ years of experience in fraud investigation, fraud analytics, or financial crime prevention.
  • 2+ years of progressive responsibilities within a financial institution or fintech environment.
  • Experience in customer service, especially in sensitive or high-impact situations. Able to be a point of escalation for members.
  • Experience with biometric risk systems, behavioral analytics, and fraud case management platforms.

Education

Associate's degree or equivalent and related work experience considered.

Licenses, Certificates, Registrations, Trainings

Ongoing training in fraud trends, digital security, and regulatory compliance encouraged.

Computer/Office Equipment Skills

  • Proficient in Windows OS, internet browsers, email platforms, and intermediate-level Microsoft Word and Excel.
  • Skilled in investigation case management software and fraud detection platforms.
  • Familiarity with SQL and able to write queries is a plus.

Managerial Responsibility

  • May assign work and supervise efforts of a small team; majority of work is performed independently.
  • Expected to lead by example and influence team performance through mentorship and collaboration.

Language Skills

  • Ability to read and interpret technical documents, regulatory guidelines, and procedural manuals.
  • Strong written and verbal communication skills for reporting, member interaction, and cross-functional collaboration.
  • Ability to present findings and recommendations to leadership and technical teams.

Other Skills and Abilities

  • High emotional intelligence and member empathy.
  • Advanced analytical and critical thinking skills.
  • Ability to adapt quickly to evolving fraud tactics and system changes.
  • Tact, diplomacy, and discretion in handling sensitive member information.
  • Strategic mindset with a focus on continuous improvement and innovation.

PHYSICAL ABILITIES / WORKING CONDITIONS

Physical Demands

Must be able to use hands to handle/feel occasionally.

Ability to stand, walk, sit, talk, and hear consistently.

Vision Requirements

Close vision (clear vision at 20 inches or less).

Distance vision (clear vision at 20 feet or more).

Color vision (ability to identify and distinguish colors).

Weight Lifted or Force Exerted

Frequently lifts up to 10 pounds, occasionally lifts up to 25 pounds.

Environmental

Typical office environment with no unusual factors.

Noise Environment

Moderate noise (business office with computers and printers, light traffic).

Mountain America Credit Union is an EEO/AA/ADA/Veterans employer.