2-4 Yrs Exp | MBA / Master’s in Quantitative Field | Data Science & Risk Analytics | Banking & Financial Services | Gurugram / Bengaluru, India | Hybrid | Full Time

Build, Deploy, and Validate Machine Learning Models to Drive Profitable Underwriting, Credit Risk, and Fraud Management at American Express

Join American Express as an Analyst in Data Science within the Credit and Fraud Risk (CFR) Center of Excellence. Operating on a hybrid work schedule in Gurugram or Bengaluru, you will leverage big data, advanced machine learning, and predictive modeling to optimize credit decisioning and combat financial fraud. You will analyze large-scale, closed-loop transaction data, develop supervised and unsupervised ML models, and communicate data-driven insights to senior business partners across global markets.

Key Responsibilities:

• Develop, deploy, and validate predictive machine learning models for risk management, fraud detection, and customer acquisition.
• Analyze massive unstructured and structured datasets to derive actionable business insights and optimize economic logic.
• Leverage closed-loop network data to engineer predictive attributes and enhance model accuracy across customer touchpoints.
• Translate complex algorithmic outcomes into structured business narratives for key stakeholders and executive leadership.
• Maintain cross-functional alignment with global analytics, engineering, and business partners to integrate models into production.

Tools/Technologies Used:

• Languages: Python, SAS, R, SQL
• Big Data & Distributed Computing: PySpark, Apache Hive, MapReduce, High-Performance Computing (HPC)
• Machine Learning Algorithms: Neural Networks, Decision Trees, Reinforcement Learning, Active Learning, Transfer Learning, Graphical Models, Gaussian Processes
• Analytics Techniques: Supervised & Unsupervised Learning, Attribute Engineering, Model Validation, Exploratory Data Analysis (EDA)