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Senior Analyst-Data Science

American Express
Posted 3 hours ago
IndiaHybridData & Analytics
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Fraud, CBO, Payments and Agentic 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 Fraud 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

  • Experience in working with Agents and associated risks

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