Analytics Engineer (Fraud Analytics)

TL;DR

Analytics Engineer (Fraud Analytics): Building and maintaining scalable data pipelines and infrastructure for fraud modeling with an accent on platform reliability, automation, and efficiency. Focus on designing robust software systems, implementing CI/CD workflows, and integrating AI-driven solutions to support the full analytics lifecycle.

Location: Must be based in the United States

Salary: $115,747–$208,344

Company

hirify.global is a global data and technology company that powers opportunities for people and businesses across financial services, healthcare, and other sectors.

What you will do

• Build scalable Python-based data pipelines and backend services for analytics workflows.
• Design software systems using object-oriented programming and sound engineering practices.
• Create and support platforms for analytics development, model training, and deployment.
• Implement and maintain CI/CD pipelines and infrastructure-as-code solutions.
• Manage cloud and on-premises analytics environments, including AWS infrastructure.
• Monitor, troubleshoot, and improve data pipelines and system reliability.

Requirements

• Must be based in the United States
• 3+ years of experience in data science, analytics, or data engineering.
• Bachelor's or advanced degree in a quantitative field.
• Proficiency in Python (PySpark, Polars, NumPy, Pandas) and familiarity with Java.
• Experience with AWS services (EC2, EMR, Airflow) and cloud security.
• Experience with CI/CD, containerization, and Linux environments.

Culture & Benefits

• Comprehensive benefits including medical, dental, vision, and 401K matching.
• Flexible work environment with options for remote, hybrid, or in-office work.
• Generous time off policy including vacation, sick leave, and 12 paid holidays.
• Inclusive, purpose-driven culture recognized as a World's Best Workplace.