ZipRecruiter

Log In

1

Fraud Detection Machine Learning Jobs in Philadelphia, PA

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 · 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.

Fraud Strategy Analyst

Malvern, PA

Develop, implement, and maintain fraud rules and detection strategies for participant transactions ... person learning, collaboration, and connection. We believe our mission-driven and highly ...

Vangard, Inc.

Fraud Strategy Senior Analyst

Malvern, PA · On-site

Continuously monitor rule performance and optimize detection effectiveness, fraud loss prevention ... Working knowledge of fraud models / machine learning concepts and model governance * Ability to ...

Citizens

Fraud Risk Analytics Manager

Philadelphia, PA · Hybrid

$106K - $130K/yr

Strong experience with fraud detection, prevention, and decisioning systems in complex environments ... Solid foundation in data science and statistical learning , including: * Classification and ...

Citizens

Fraud Risk Analytics Manager

Philadelphia, PA · Hybrid

$106K - $130K/yr

Strong experience with fraud detection, prevention, and decisioning systems in complex environments ... Solid foundation in data science and statistical learning , including: * Classification and ...

Citizens

Fraud Risk Analytics Manager

Philadelphia, PA · Hybrid

$106K - $130K/yr

Strong experience with fraud detection, prevention, and decisioning systems in complex environments ... Solid foundation in data science and statistical learning , including: * Classification and ...

Citizens

Fraud Risk Analytics Manager

Philadelphia, PA · Hybrid

$106K - $130K/yr

Strong experience with fraud detection, prevention, and decisioning systems in complex environments ... Solid foundation in data science and statistical learning , including: * Classification and ...

Vangard, Inc.

Senior Manager Purple Team

Malvern, PA · On-site

Serve as the primary liaison between OSFT, CSOC, Threat Detection Engineering, Fraud Detection, and ... person learning, collaboration, and connection. We believe our mission-driven and highly ...

previous pagenext page

Showing results 21-40

All JobsFraud Detection Machine Learning JobsFraud Detection Machine Learning Jobs in Philadelphia, PA

Fraud Detection Machine Learning information

See Philadelphia, PA salary details

$10

$18

$27

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 Philadelphia, PA is $18.22, according to ZipRecruiter salary data. Most workers in this role earn between $15.05 and $19.42 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 Philadelphia, PA? For Fraud Detection Machine Learning jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Fraud Detection Machine Learning jobs in Philadelphia, PA look for? The top searched job categories for Fraud Detection Machine Learning jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Fraud Detection Machine Learning jobs? Cities near Philadelphia, PA with the most Fraud Detection Machine Learning job openings:
Fraud Detection Machine Learning jobs near you

Principal Machine Learning Engineer

Apetan Consulting llc

Philadelphia, PA • On-site

$80 - $150/hr

Contractor

Posted 25 days ago

Job description

Title: Principal Machine Learning Engineer

Duration: 6 Mos C2H (without sponsorship)

Location: Hybrid in Philadelphia, PA onsite Tue & Wed each week (Local candidates preferred but, those willing to relocate are acceptable)

Principal Machine Learning Engineer to serve as a hands-on technical leader for machine learning, predictive modeling, scoring, decisioning, and applied AI initiatives. This role will primarily focus on building, validating, deploying, and improving machine learning models, while also bringing principal-level judgment to problem definition, model design, stakeholder engagement, and production readiness.

Hands-On Model Development

  • Build, test, validate, and improve machine learning models for scoring, prediction, prioritization, risk detection, engagement, intervention targeting, and decision support.
  • Perform exploratory data analysis, data quality assessment, feature engineering, model training, model selection, and performance evaluation.
  • Develop practical ML models that balance predictive performance, explainability, stability, maintainability, and business usefulness.
  • Work with structured, semi-structured, and operational data to create model-ready datasets and reusable features.
  • Use tools such as Python, SQL, Spark, Databricks, MLflow, scikit-learn, XGBoost, or similar platforms and libraries.
  • Move quickly from data exploration to prototype to validated model to production-ready capability.

 

Required Qualifications

  • Professional experience in machine learning, data science, software engineering, analytics engineering, applied AI, or related technical fields.
  • 5+ years of hands-on machine learning model development experience, including feature engineering, model training, validation, evaluation, and iteration.
  • 3+ years of experience deploying, operationalizing, or supporting models in production or business-critical environments.
  • Strong hands-on experience with Python and SQL.
  • Experience with modern ML and data platforms such as Databricks, Spark, MLflow, Snowflake, Azure, AWS, or similar technologies.
  • Strong understanding of model evaluation, calibration, thresholding, score interpretation, monitoring, drift, retraining, and production ML lifecycle management.
  • Experience translating ambiguous business problems into concrete ML designs, model requirements, validation plans, and measurable outcomes.
  • Ability to explain model behavior, model performance, assumptions, limitations, and tradeoffs to both technical and non-technical stakeholders.
  • Strong engineering discipline, including clean code, reproducibility, versioning, testing, documentation, and maintainability.
  • Ability to work independently as a senior hands-on contributor while also providing technical leadership and modeling judgment.

Scoring, Scorecards, and Transparent Models

Production ML and MLOps

Product and Rapid-Build Execution

Generative AI and AI Automation

Requirement Shaping and Stakeholder Partnership