American Express, a global leader in financial services, is currently seeking qualified candidates for the position of Analyst-Data Science in Gurgaon and Bengaluru. Ideal applicants should hold an MBA or a Master’s degree in Economics, Statistics, Computer Science, or related fields. With an experience requirement ranging from 0 to 30 months, this role offers opportunities for fresh graduates and those with some prior experience in data science. As an Analyst-Data Science at American Express, you will be part of a dynamic team driving data-driven insights and innovation to enhance business strategies and customer experiences.
Company Name: American Express
Job Role: Analyst-Data Science
Education Required: MBA, Master’s Degree In Economics, Statistics, Computer Science Or related fields
Experience Required: 0-30 months
Job Location: Gurgaon, Bengaluru
Role and Responsibilities:
- Understand the core business of AXP and the levers behind various decisions.
- Analyze large amounts of data to derive business insights and create innovative solutions.
- Leverage the power of closed loop through the Amex network to make decisions more intelligent and relevant.
- Innovate with a focus on developing newer and better approaches using big data & machine learning solutions.
- Clear articulation and structuring of business findings across prospect and customer domains to the leadership and key partners.
- Maintain an external lens and be aware of developments in the field of Finance/Payments/Analytics etc.
Required Skills and Qualifications:
- MBA, Master’s Degree In Economics, Statistics, Computer Science, Or related fields.
- 0-30 months of experience in analytics, big data workstreams (24-48 months of experience for Sr. Analyst Req)
- Ability to drive project deliverables to achieve business results.
- Ability to work effectively in a team environment.
- Strong communication and interpersonal skills.
- Innovative problem solver with the ability to learn quickly and work independently with complex, unstructured initiatives.
- Ability to Integrate with Cross-Functional Business Partners Worldwide.
- SAS, R, Python, Hive, Spark, SQL.
- Unsupervised and supervised techniques -: active learning, transfer learning, neural models, Decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, Map Reduce techniques, attribute engineering.
- Expertise in Coding, Algorithm, High Performance Computing.
