About this role
Compromise Decision Science Team of American Express is looking for an Senior Analyst who would be actively involved in developing, refining and implementing ML models for Compromise Fraud Risk Decision Sciences domain.
Compromise Decision sciences team is involved in developing solutions for preventing fraud arising from compromised card credentials. This involves developing sophisticated ML models, feature engineering, graph based solutions to curb fraud losses arising from cards that were compromised across the customer journey.
- Graduate or postgraduate degree in Statistics, Mathematics, Economics, Engineering, Management, Computer Science, or a related quantitative discipline from a recognized institution.
- 2–3 years of relevant experience in data science, advanced analytics, machine learning, or predictive modeling.
- Strong programming skills in Python and PySpark, with hands-on experience in data manipulation, statistical analysis, and machine learning model development.
- Solid understanding of machine learning and deep learning techniques, with exposure to Graph Neural Networks, graph-based algorithms, Transformer architectures, or related advanced AI methodologies.
- Familiarity with deep learning frameworks such as PyTorch or TensorFlow and cloud computing environments such as Google Cloud Platform.
- Experience working with large-scale datasets, feature engineering, data preprocessing, and model evaluation techniques.
- Strong problem-solving skills, analytical rigor, and the ability to translate complex business requirements into effective technical solutions.
- Excellent written and verbal communication skills, with the ability to present analytical insights and recommendations to diverse stakeholders.
- Demonstrated ability to exercise sound judgment, work collaboratively, and deliver high-quality analytical solutions in a dynamic business environment.
- Shift Timings : Mon - Wed 1:00 PM -9:30 PM ; Thurs 11:00 AM- 7:30 PM ; Friday - 8:30 AM -5 PM