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Software Engineer Fraud Detection Jobs in Texas (NOW HIRING)

Develops, enhances, and maintains fraud detection and prevention models across multiple fraud ... Engineering, and Fraud Operations. Ensures production accuracy, operational readiness, user ...

... fraud detection and prevention while operating within a highly regulated environment. In this role ... Mentor and coach software engineers and promote engineering best practices * Collaborate with and ...

Mine application data to develop segmentation to improve fraud detection and minimize impact to ... Economics, Engineering or other quantitative, business, or technical discipline, or equivalent ...

Mine application data to develop segmentation to improve fraud detection and minimize impact to ... Economics, Engineering or other quantitative, business, or technical discipline, or equivalent ...

Software Engineer III

San Antonio, TX · On-site

$51.75 - $69.75/hr

If so, being a Software Engineer III at Frost could be the job for you. At Frost, it's about more ... Understanding of secure coding practices and familiarity with fraud detection and prevention ...

This individual will partner closely with Product, Engineering, Fraud Strategy, and Operations ... Required Qualifications * 5+ years of Business Analyst experience supporting enterprise software ...

Develops, enhances, and maintains fraud detection and prevention models across multiple fraud ... Engineering, and Fraud Operations. Ensures production accuracy, operational readiness, user ...

Software Engineer III

Austin, TX

$57 - $76.50/hr

If so, being a Software Engineer III at Frost could be the job for you. At Frost, it's about more ... Understanding of secure coding practices and familiarity with fraud detection and prevention ...

Software Engineer III

San Antonio, TX · On-site

$51.75 - $69.75/hr

If so, being a Software Engineer III at Frost could be the job for you. At Frost, it's about more ... Understanding of secure coding practices and familiarity with fraud detection and prevention ...

Software Engineer III

Fort Worth, TX · On-site

$55 - $74/hr

If so, being a Software Engineer III at Frost could be the job for you. At Frost, it's about more ... Understanding of secure coding practices and familiarity with fraud detection and prevention ...

Software Engineer III

Houston, TX · On-site

$55 - $73.75/hr

If so, being a Software Engineer III at Frost could be the job for you. At Frost, it's about more ... Understanding of secure coding practices and familiarity with fraud detection and prevention ...

Software Engineer III

Dallas, TX · On-site

$57 - $76.50/hr

If so, being a Software Engineer III at Frost could be the job for you. At Frost, it's about more ... Understanding of secure coding practices and familiarity with fraud detection and prevention ...

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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 Texas? For Software Engineer Fraud Detection jobs in Texas, the most frequently searched job titles are:
What job categories do people searching Software Engineer Fraud Detection jobs in Texas look for? The top searched job categories for Software Engineer Fraud Detection jobs in Texas are:
What cities in Texas are hiring for Software Engineer Fraud Detection jobs? Cities in Texas with the most Software Engineer Fraud Detection job openings:
Asset & Wealth Management - Engineering - Fraud Detection & AI/ML Strategy - Vice President - Ric...

Asset & Wealth Management - Engineering - Fraud Detection & AI/ML Strategy - Vice President - Ric...

Goldman Sachs, Inc.

Richardson, TX

$163K - $210K/yr

Other

Posted 9 days ago


Goldman Sachs rating

8.2

Company rating: 8.2 out of 10

Based on 26 frontline employees who took The Breakroom Quiz

30th of 142 rated banks


Job description

Role Purpose

The VP of Fraud Detection Engineering will lead the strategic development and implementation of advanced AI and Machine Learning models to safeguard the Consumer Deposit business. This leader is responsible for architecting a real-time fraud detection ecosystem that leverages multi-dimensional signals to identify and mitigate fraud vectors across the entire customer lifecycle. From initial acquisition and account opening to complex money movement and ongoing account management, you will be the primary technical authority for defending against synthetic fraud, third-party account takeovers (ATO), and sophisticated financial crimes.

Key Responsibilities

1. AI/ML Model Strategy & Implementation

  • End-to-End Fraud Modeling: Lead the design, training, and deployment of ML models (e.g., Gradient Boosted Trees, Transformers, Graph Neural Networks) to detect anomalies in real-time.
  • Signal Orchestration: Develop frameworks to ingest and synthesize multiple fraud signals, including behavioral biometrics, device fingerprinting, geolocation, and cross-platform transactional data.
  • Real-Time Insights: Architect low-latency inference pipelines that provide immediate "go/no-go" decisions for high-risk events like account applications and large-value transfers.

2. Lifecycle Fraud Prevention

  • Acquisition & Onboarding: Implement robust models to identify synthetic identities and fraudulent applications during the customer acquisition phase.
  • Money Movement Security: Define technical standards for monitoring ACH, wire, and P2P transfers to detect unauthorized activity and "mule" account patterns.
  • Account Takeover (ATO) Defense: Develop sophisticated behavioral baselines to identify 3rd-party account takeovers and session hijacking attempts.

3. Engineering Excellence & Scalability

  • Scalable Infrastructure: Oversee the engineering of high-throughput data pipelines capable of processing millions of daily events with sub-second latency.
  • Feature Engineering: Lead the development of a centralized feature store to ensure consistency between model training and real-time production environments.
  • Model Governance: Establish rigorous back-testing, A/B testing, and monitoring frameworks to track model drift and ensure high precision/recall ratios.

4. Strategic Leadership & Collaboration

  • Thought leadership: Stay ahead of emerging fraud trends (e.g., GenAI-enabled deepfakes, automated bot attacks) by fostering a culture of continuous research and rapid prototyping.
  • Cross-Functional Alignment: Partner with the Chief Risk Officer (CRO), Product Leads, and Legal/Compliance teams to align technical fraud roadmaps with business growth and regulatory requirements.
  • Team Mentorship: Build and lead a world-class team of ML engineers, data scientists, and backend engineers specializing in financial security.

Required Qualifications & Skills

Technical Expertise

  • Engineering Leadership: 8+ years of experience in software engineering or data science, with at least 6 years in a senior leadership role within Fraud or Risk Tech.
  • ML Mastery: Deep expertise in supervised and unsupervised learning, specifically for anomaly detection and classification in imbalanced datasets.
  • Tech Stack: Proficiency in Python, PySpark, and modern ML frameworks. Experience with cloud-native AI services (AWS SageMaker, GCP Vertex AI).
  • Domain Knowledge: Strong understanding of banking protocols (ACH, ISO 20022) and identity verification standards (KYC/AML).

Strategic Leadership

  • Analytical Rigor: Proven track record of reducing fraud loss rates while maintaining a seamless, low-friction customer experience.
  • Stakeholder Management: Ability to translate complex model performance metrics into clear business impact for executive leadership.
  • Risk Mindset: Deep understanding of the trade-offs between false positives (customer friction) and false negatives (fraud loss).

Education

  • Master's in Computer Science, Statistics, Mathematics, or a related quantitative field.

ABOUT GOLDMAN SACHS

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. 

We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

The Goldman Sachs Group, Inc., 2023. All rights reserved.

Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.


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About Goldman Sachs

Sourced by ZipRecruiter

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869