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Fraud Detection Machine Learning Jobs in Pennsylvania

Gather AI

Director of Machine Learning

Pittsburgh, PA · On-site +1

About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of ... Drive improvements to core computer vision models (object detection, segmentation, OCR) used across ...

Gather AI

Director of Machine Learning

Pittsburgh, PA

About the Team You'll lead the Machine Learning and FPT teams, working closely with the Director of ... Drive improvements to core computer vision models (object detection, segmentation, OCR) used across ...

Vanguard Group

Senior Machine Learning Engineer

Malvern, PA · On-site

$102K - $140K/yr

Implement model monitoring for performance, drift detection, data quality, and operational health ... Experience in software engineering, machine learning engineering, data engineering, or a related ...

Vangard, Inc.

Senior Machine Learning Engineer

Malvern, PA

$102K - $140K/yr

Implement model monitoring for performance, drift detection, data quality, and operational health ... Experience in software engineering, machine learning engineering, data engineering, or a related ...

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All JobsFraud Detection Machine Learning JobsFraud Detection Machine Learning Jobs in Pennsylvania

Fraud Detection Machine Learning information

See Pennsylvania salary details

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

As of Aug 12, 2026, the average hourly pay for fraud detection machine learning in Pennsylvania is $18.10, according to ZipRecruiter salary data. Most workers in this role earn between $14.95 and $19.28 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 Pennsylvania? For Fraud Detection Machine Learning jobs in Pennsylvania, the most frequently searched job titles are:
What job categories do people searching Fraud Detection Machine Learning jobs in Pennsylvania look for? The top searched job categories for Fraud Detection Machine Learning jobs in Pennsylvania are:
What cities in Pennsylvania are hiring for Fraud Detection Machine Learning jobs? Cities in Pennsylvania with the most Fraud Detection Machine Learning job openings:
Fraud Detection Machine Learning jobs near you

Director of Machine Learning

Gather AI

Pittsburgh, PA • On-site, Remote

Full-time

Re-posted 11 days ago

Job description

About Us
Are you ready to build the future of supply chain? At Gather AI, we're not just creating software; we're pioneering a new era of warehouse intelligence. We've developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining "on-time, in full" delivery.
If you're looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We're leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.
About the Team
You'll lead the Machine Learning and FPT teams, working closely with the Director of Cloud Engineering and Director of Autonomy. Cross-departmentally, you'll collaborate with Product and Business leadership to translate ML capabilities into product value. This is a high-visibility role with a direct line to executive leadership and significant influence over product direction.
About the Role
We are looking for a Director of Machine Learning to define our ML strategy, lead our computer vision organization, and drive the next phase of ML maturity at Gather AI. You will assess existing ML and CV capabilities, identify gaps and opportunities, and establish a clear technical vision for how machine learning will power our warehouse intelligence platform over the next 12-18 months.
The ideal candidate brings deep computer vision expertise, a track record of shipping production ML systems, and the leadership experience to build and scale a world-class ML team.
What You'll Do
  • Define and own the ML strategy and technical roadmap for Gather AI, aligned with product and business objectives
  • Lead and grow the Machine Learning and FPT teams, establishing a culture of rigor, experimentation, and production-quality delivery
  • Drive improvements to core computer vision models (object detection, segmentation, OCR) used across our drone and MHE Vision products
  • Build out MLOps infrastructure - model training pipelines, deployment, monitoring, and CI/CD for ML workloads
  • Collaborate with the Director of Cloud Engineering and Director of Autonomy to ensure ML systems integrate seamlessly into the broader platform
  • Partner with Product and Operations to translate customer needs into ML-driven product capabilities

What You'll Need
  • 10+ years building and scaling production ML or computer vision systems
  • 5+ years managing and growing ML engineering teams
  • Deep expertise in computer vision: object detection, image segmentation, OCR, and CNN architectures
  • Strong Python and PyTorch (or TensorFlow) proficiency, plus a track record of shipping ML models to production at scale
  • MS or PhD in Computer Science, Machine Learning, or a related field (strong industry track record considered in lieu of advanced degree)

Nice to Have
  • Experience with drone, robotics, or autonomous systems perception
  • Edge ML deployment experience (ONNX, TensorRT, mobile/embedded inference)
  • Familiarity with warehouse, logistics, or supply chain domain
  • Experience with AWS or GCP ML services (SageMaker, Vertex AI)

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