Summary: You would get chance to design and implement scalable solutions to optimize fraud detection systems, spanning model development, feature engineering, and rule-based systems. You will collaborate closely with cross-functional teams, including data scientists, engineers, and product managers, to ensure our platform sets a new global standard for efficacy and innovation. You will address critical business challenges, develop advanced automation frameworks, and integrate cutting-edge machine learning techniques to enhance decision-making capabilities. By joining us, you will not only contribute to fraud detection efforts but leave a lasting impact on the financial security of millions of users around the globe.
Responsibilities:
Redesign and optimize MLOps and decision platform for fraud detection
Architect large-scale big-data infrastructure to enable use of cutting-edge machine learning models for real-time fraud prevention.
Collaborate with data scientists and platform engineers to automate workflow
Provide solutions that ensure compliance, security, and maintainability across the fraud detection ecosystem.
Work with high-dimensional datasets and leverage tools like Python, PySpark, and Big Query to develop robust workflows for fraud signal detection.
Standardize rules and decision processes while enabling dynamic rule updates and analytics within the fraud detection platform.
Collaborate across multidisciplinary teams in engineering, product development, and data science to scale solutions globally.
Will work with Core Automation team's Tech leads/managers closely
Rebuild together with Engineer teams on our next generation risk platform (NGRP)
We have a tight timeline to meet decision engine adoption plan
You will be part of our pioneer working team launching our NGRP
Requirements:
At least 6 years above
MS above
STEM only
Python code, Big Query
Understand the production systems architect overview
