Senior Analyst-Data Science
Summary
Build and refine machine-learning models to detect fraud and manage risk for American Express payments, using Python, PySpark, and cloud platforms.
Fraud, CBO and Payments Risk Decision Science Team of American Express is looking for a tenured Analyst or Sr.Analyst who would be actively involved in developing, refining and implementing ML models for Payments Risk Decision Sciences domain.
Responsible for:
- Leverage advanced ML techniques to innovate for the next generation of models and drive business growth
- Conduct case reviews to generate insights for improving the model performance and decision-making processes
- Collaborate with relevant stakeholders to ensure alignment of analytical and modeling efforts with business objectives, effectively managing stakeholder expectations and communication throughout the project lifecycle
- Bring in ideas by incorporating external perspectives through reading research papers and identify appropriate use cases to enhance model development and innovation.
Minimum Qualifications
- Graduate/Post Graduate Degree in Statistics/Mathematics/Economics/ Engineering/Management from a reputed institute.
- 2+ years relevant CFR experience in Analytical/Modelling Skills
- Proficiency in data analysis and programming languages such as Python, Hive, PySpark.
- Strong coding skills and hand-on experience with advanced Machine Learning, Deep Learning, AI algorithms
- Familiarity with cloud computing platforms like Google Cloud for model training.
- Experience in handling large datasets and implementing data preprocessing techniques
- Excellent communication and presentation skills, with the ability to translate business problems into technical solutions and explain complex technical concepts to non-technical stakeholders.
- Demonstrated ability to provide insight and accurate judgment in addressing and resolving business challenges and opportunities
Preferred Qualifications
- Knowledge of Amex platforms is preferred
- Experience in building and deploying models