Senior Analyst - Data Science

AMERICAN EXPRESS INNOVATION LABORATORIES LIMITED (SINGAPORE BRANCH)

Singapore

On-site

SGD 70,000 - 120,000

Full time

2 days ago
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Job summary

AMERICAN EXPRESS INNOVATION LABORATORIES LIMITED (SINGAPORE BRANCH) is seeking an Analyst, AI/ML to lead hands-on Generative AI initiatives and rapid prototyping. You will work with cross-functional partners to translate real business challenges into scalable data-driven solutions.

The role emphasizes PoC development, model training, and deployment, with strong emphasis on collaboration with Technology and Engineering teams to deliver impactful AI capabilities.

Qualifications

  • Advanced degree in CS/Engineering/Statistics/Math.
  • Hands-on ML/NLP/Generative AI experience in prototype to solution.
  • Strong collaboration and communication with cross-functional teams.

Responsibilities

  • Develop and implement PoC prototypes for AI/ML and Generative AI.
  • Write clean, documented code for data processing, model training, and deployment.
  • Collaborate with Technology to integrate solutions into existing systems.
  • Conduct experiments to evaluate model performance and optimize for scalability.
  • Stay updated on AI/ML trends and share knowledge with the team.
  • Engage with Engineering to enhance integration and user engagement.

Skills

Python
Java
C++
TensorFlow
PyTorch
scikit-learn
NLP
Generative AI
Deep Learning
Data processing

Education

Master's or PhD in quantitative discipline

Tools

Data processing libraries

Job description

Roles & Responsibilities

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.

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

Responsibilities
  • 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
Qualifications
  • 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.
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