You will be part of an energetic A.I./Machine Learning cross-functional team, collaborating with various business/product partners (e.g. Credit, Fraud, Risk, Web, Mobile, Marketing, Enterprise Automation, etc.) to drive a cohesive set of solutions enabling the ever-growing strategic capabilities in the AI field.
This role resides within American Express Technology (AET) – Enterprise Services Decision Science Center of Excellence (CoE).
Role Overview:
As an Analyst, AI/ML, you will play a crucial role in the development and implementation of cutting-edge Generative AI solutions that address significant business challenges. This role focusses on hands-on implementation, rapid prototyping, and collaboration with cross-functional teams to deliver innovative solutions that address real business challenges. Your contributions will directly impact our strategic goals, driving innovation and excellence in customer interactions.
Develop and implement Proof of Concepts (PoCs) prototypes for AI/ML and Generative AI solutions, ensuring alignment with business objectives.
Write clean, efficient, and well-documented code for data processing, model training, and deployment.
Collaborate with the Technology team to integrate solutions into our existing systems and platforms.
Conduct experiments to evaluate model performance and optimize algorithms for scalability.
Stay abreast of the latest trends in AI/ML and actively share knowledge and insights to contribute to the collective growth and technical proficiency of the team.
Collaborate with the Engineering team to integrate solutions into our existing systems and platforms, enhancing functionality and user engagement.
Actively participate in technical discussions and forums across Amex
Advanced degree (Master/ PhD) in quantitative discipline (e.g., Computer Science, Engineering, Statistics, Mathematics).
Strong programming skills in at least one language (Python, Java, C++, etc.)
Familiarity with machine learning libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and data processing libraries
- Extensive experience in machine learning, NLP and Generative AI, with a demonstrated ability to build scalable prototypes from inception to solution.
- Proven expertise in applying deep learning and NLP techniques to solve complex problems, with a portfolio of projects on real-world problems.
- Solid understanding of Large Language Models and practical experience with Generative AI
- Strong ability to translate real-world problems to data science problems.
- Excellent communication and collaboration skills, with the ability to collaborate effectively with both technical and non-technical teams.