Analytics Engineer (Remote)
Core
Build and maintain scalable data infrastructure, pipelines, and platforms to support fraud analytics, model training, and deployment for Experian's fraud business.
Role type
Senior Analytics Engineer (Fraud Infrastructure)
Builds
Python-based data pipelines, backend services, and analytics platforms for fraud modeling workflows.
Domain
Financial services / Fraud detection / Data Engineering
Deliverable
production ML models | infrastructure
Required skills
Python (PySpark, Polars, NumPy, Pandas), Object-Oriented Programming, AWS (EC2, EMR, Airflow), CI/CD, Infrastructure as Code, Containerization, UNIX/Linux, Machine Learning workflows, Feature engineering
Preferred skills
AI/ML solution evaluation, Cloud security best practices, Cross-functional collaboration
Technologies
Python, PySpark, Polars, NumPy, Pandas, Java, AWS, EC2, EMR, Airflow, Docker/Kubernetes (implied by containerization), CI/CD tools
Responsibilities
Build scalable data pipelines and backend services; Design software systems using OOP; Create and support platforms for analytics development and model deployment; Implement and maintain CI/CD pipelines and IaC; Manage cloud and on-premises analytics environments; Monitor and improve pipeline performance and reliability; Support ML workflows including feature engineering and model deployment.
Seniority
Mid-Senior, hands-on IC