Senior Analyst-Data Science

Credit and Fraud Risk Organization (CFR) within American Express has the mission of minimizing credit and fraud losses while promoting business growth and delivering superior customer service. In India, the CFR CoE (Center of Excellence) team is involved in developing predictive models, business strategies, capabilities, and platforms for driving the above outcomes across all portfolios for American Express globally. Our Decision Science teams use industry leading modelling and AI practices to predict customer behavior. We develop, deploy, and validate predictive models and support the use of models in economic logic to enable profitable decisions across credit, fraud, marketing and servicing optimization engines.

• Masters/PhDs in a quantitative field (Computer Science, Statistics, Economics, Mathematics, Physics, Operation Research etc.) or MBA with hands-on experience leveraging sophisticated analytical and machine learning techniques.
• Expertise in an analytical language (Python, R or the equivalent), and experience with databases (Hive, SQL, or the equivalent).
• Deep understanding of machine learning/statistical algorithms such as deep learning and boosting. Experience with data visualization is a plus.
• Minimum 2 years of experience in Modeling
• Demonstrated ability to frame business problems into mathematical programming problems, leverage external thinking and tools (from academia and/or other industries) to engineer a solution and deliver business insights.
• Ability to work effectively in a team environment.
• Independent thinker who s organized, has great attention to detail, and can multi-task.
• Strong communication skills
• Ability to learn quickly and work independently with sophisticated, unstructured initiatives.
• Ability to integrate with cross-functional business partners worldwide.
• Proficient in presentation tools, including Excel and PowerPoint

• Work with massive amounts of customer, bureau and 3rd party data using sophisticated tools in an industry leading Big Data environment.
• Build everything from basic reports to advanced machine learning models and algorithms to drive improvements to our customer s experiences.
• Evaluate new structured and unstructured data sources and modelling techniques/algorithms to enhance model predictions.
• Develop insights into customer behavior and introduce new approaches to transform complex behavioral data into actionable information.
• Innovate with a focus on developing newer and better approaches using big data & machine learning solutions.

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