American Express, a renowned global financial services company, is currently seeking candidates for the position of Analyst-Data Science. This role is an excellent opportunity for individuals with a postgraduate degree in Statistics, Mathematics, Economics, Engineering, or Management. American Express, known for its commitment to innovation and excellence, values the diverse skill set that candidates from these academic backgrounds bring to the field of data science. The position requires 0-3 years of experience, making it an inclusive opportunity for both fresh graduates and those with some professional exposure. Located in the bustling business hub of Gurgaon, this role provides an exciting environment for individuals looking to contribute to cutting-edge data science projects within the financial services sector.
Company Name: American Express
Job Role: Analyst-Data Science
Education Required: Postgraduate in Statistics/Mathematics/Economics/ Engineering/Management
Experience Required: 0-3 years
Job location: Gurgaon
Role and Responsibilities:
- Deliver fraud prevention solutions for Accertify’ s clients.
- Understand the key drivers / behaviors associated with different types of Fraud.
- Being abreast of the latest fraud trends and problems being faced by the industry and Accertify clients.
- Drive Modeling innovation: Develop new and enhance existing models by utilizing the best-in-class machine learning / AI techniques.
- Elevate Data Science: Perform Feature Engineering using data from clients spanning various industries across the globe to improve model’s risk discrimination or improve economics over and above existing framework.
- Partner and collaborate with multiple Accertify colleagues to implement models & develop Capabilities that will help in more optimal decision and drive revenue.
Required Skills Qualification:
- 0-3 years with relevant experience in the Analytics/ Modelling/ Decision Science domain.
- Postgraduate in Statistics/Mathematics/Economics/ Engineering/Management.
- Data Science/Machine Learning/Artificial Intelligence: Gradient Boosting Machines, Deep Learning, Unsupervised Techniques, Decision Trees etc.
- Understanding of Advanced Statistical Techniques and Key model performance metrics ex. Data Correlation; AUC/GINI, Precision, Recall.
- Knowledge of R, Python, PySpark, SAS, SQL; Advanced Excel and PowerPoint.