1

Software Engineer Fraud Detection Jobs in Pennsylvania

Fraud Hub Lead Engineer

Pittsburgh, PA · On-site

$99K - $131K/yr

Required : • 10+ years of software engineering experience, with at least 5 years delivering Fraud ... detection, or real-time risk decisioning. • Demonstrated success leading and scaling global ...

The Fraud Specialist plays a vital front-line role in First Commonwealth's fraud detection and ... software platforms. 7. Experience with fraud platforms (e.g., Verafin). 8. Familiarity with ...

Reviews fraud alerts and reports generated by computer software (neural networks) and proprietary databases designed to detect fraud. Evaluates account activity to validate fraud and implements ...

New

Reviews fraud alerts and reports generated by computer software (neural networks) and proprietary databases designed to detect fraud. Evaluates account activity to validate fraud and implements ...

New

Reviews fraud alerts and reports generated by computer software (neural networks) and proprietary databases designed to detect fraud. Evaluates account activity to validate fraud and implements ...

New

This role is responsible for building and scaling a threat-informed validation program that partners Offensive Security, the CSOC, Detection Engineering, and Fraud Detection teams to continuously ...

Software Engineer

Philadelphia, PA · On-site

$105K - $164K/yr

Software Engineer, Entry Level * Software Engineer, Mid Level * Software Engineer, Senior Level ... Adequate vision is necessary to read technical manuals, identify color-coded systems, and detect ...

... Software based on reader feedback demonstrating its across-the-board success with customers in the three core areas of Client Gartner Magic Quadrant Leaders Quadrant for 2011 Web Fraud Detection Fast ...

... Software based on reader feedback demonstrating its across-the-board success with customers in the three core areas of Client Gartner Magic Quadrant Leaders Quadrant for 2011 Web Fraud Detection Fast ...

next page

Showing results 1-20

Software Engineer Fraud Detection information

What does a software engineer 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.

How does a software engineer 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 the key skills and qualifications needed to thrive as a software engineer 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.

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 popular job titles related to Software Engineer Fraud Detection jobs in Pennsylvania?

For Software Engineer Fraud Detection jobs in Pennsylvania, the most frequently searched job titles are:

What job categories do people searching Software Engineer Fraud Detection jobs in Pennsylvania look for?

The top searched job categories for Software Engineer Fraud Detection jobs in Pennsylvania are:

What cities in Pennsylvania are hiring for Software Engineer Fraud Detection jobs?

Cities in Pennsylvania with the most Software Engineer Fraud Detection job openings:

Fraud Hub Lead Engineer

Pittsburgh, PA • On-site

BNY
10K+ employees

$99K - $131K/yr

Full-time

Re-posted 4 days ago


Job description

Job Summary:
BNY is a leading global financial services company influencing nearly 20% of the world’s investible assets. They are seeking a Fraud Hub Lead Engineer to lead the global engineering strategy and execution for BNY’s Fraud Hub, focusing on fraud detection, prevention, and response platforms while ensuring secure and scalable systems.
Responsibilities:
• Define and execute the global engineering strategy for BNY’s Fraud Hub, acting as the single engineering owner for Fraud platforms, standards, and delivery.
• Build, lead, and inspire a high‑performing global engineering organization with strong technical depth, clear ownership, and a relentless focus on quality and outcomes.
• Establish engineering standards for availability, resiliency, security, model risk management, and operational excellence across all Fraud technology.
• Own the end‑to‑end architecture, build, and operation of scalable, real‑time Fraud detection and decisioning platforms.
• Design and operate streaming, event‑driven systems for real‑time Fraud detection, monitoring, and response across high‑volume payment and transaction flows.
• Integrate emerging AI‑driven systems for anomaly detection, behavior analysis, alert prioritization, investigation, and remediation. Solutions must include biometrics, video and voice analytics.
• Develop retrospective and “after‑event” analytics capabilities to continuously improve models, controls, and defenses against emerging Fraud threats.
• Anticipate new Fraud vectors and proactively evolve platforms, data, and AI capabilities using a 360 mindset to stay ahead of the threat landscape.
• Provide full lifecycle ownership for Fraud platforms, including build, run, resiliency, incident response, and continuous improvement.
• Establish, track, and report KPIs and OKRs including uptime, MTTR, change success rate, SLA adherence, throughput, and operational risk indicators.
• Champion modern DevSecOps and MLOps practices, ensuring safe, repeatable, and auditable deployment of software and AI into production.
• Partner closely with Risk, Compliance, Cyber, Legal, Operations, and Product teams to translate regulatory and risk requirements into actionable engineering outcomes.
• Serve as a trusted engineering leader to senior executives and stakeholders, influencing investment, prioritization, and strategic direction.
• Provide a firmwide hub of Fraud engineering expertise, intelligence, and best practices, enabling consistent, high‑quality outcomes across the enterprise.
Qualifications:
Required:
• 10+ years of software engineering experience, with at least 5 years delivering Fraud, Financial Crime, or large-scale risk analytics platforms.
• Proven experience building and deploying AI/ML-driven solutions for Fraud detection, anomaly detection, or real-time risk decisioning.
• Demonstrated success leading and scaling global engineering teams responsible for mission-critical, regulated technology platforms.
• Hands-on technical credibility and use of emerging AI tools: able to design systems, review code, evaluate architectures, and build working prototypes when needed.
• Experience operating AI in production environments, including model lifecycle management, monitoring, drift detection, explainability, and governance.
• Strong understanding of modern distributed systems, event-driven architectures, streaming platforms, and cloud-native design patterns.
• Familiarity with cybersecurity practices, identity and access management, logging/SIEM integrations, and secure-by-design engineering.
Preferred:
• Experience working with industry Fraud platforms, vendor ecosystems, or participation in industry working groups.
• Experience operating in highly regulated financial environments and partnering with Compliance, Risk, and Audit teams.
• Strong executive communication and stakeholder-management skills; comfortable influencing across lines of business and technology.
• You are energized by building platforms, not just managing teams.
• You bring a forward-looking mindset — continuously asking what's next and how we get ahead.
• You value engineering excellence, operational rigor, and measurable outcomes.
• You thrive in complex, enterprise environments and can turn ambiguity into execution.
Company:
BNY is a global financial services platforms company at the heart of the world’s capital markets. Founded in 1784, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.