Senior Data Scientist, Real-Time Personalization & AI on AWS

CHARLES & KEITH GROUP; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

CHARLES & KEITH GROUP is seeking a Senior Data Scientist to build and operate production ML on AWS, focusing on a contextual multi-armed bandit personalizing homepage, listings, and cart experiences with fast real-time endpoints. You will also drive generative AI applications for retail, including RAG over catalogs and agentic workflows.

The role spans demand forecasting, pricing, search, recommendations, and segmentation, with emphasis on production discipline, CI/CD for ML, and robust

Qualifications

• Bachelor’s degree in CS/ML/DS or related field.
• 4+ years of applied ML in production (7+ for Senior) with personalization/recSys at consumer scale.
• Hands-on AWS/SageMaker end-to-end (training jobs, pipelines, feature store, model monitor).
• Broader AWS stack: S3, Glue, Athena, Kinesis, Lambda, IAM, KMS; MLOps: CI/CD for ML, IaC, containers.

Responsibilities

• Contextual bandit personalization on AWS for flagship project (homepage, listings, product, cart).
• Engineer behavioral features from clickstream and warehouse data; design reward functions and exploration policies.
• Deliver end-to-end on SageMaker AI: training jobs, pipelines, feature store, model registry, real-time endpoints (<100 ms).
• Validate uplift via A/B experiments; transition ownership from vendor to production.

Skills

Python

SQL

PyTorch/TensorFlow

SageMaker

AWS

MLOps

AB testing

Reinforcement learning

Vector databases

LangChain

Hugging Face

TensorFlow

Education

Bachelor’s Degree in Computer Science / ML / DS

Tools

Amazon SageMaker

Hugging Face

LangChain

TensorFlow

PyTorch

Job description

CHARLES & KEITH GROUP is seeking a Senior Data Scientist to build and operate production ML on AWS, focusing on a contextual multi-armed bandit personalizing homepage, listings, and cart experiences with fast real-time endpoints. You will also drive generative AI applications for retail, including RAG over catalogs and agentic workflows.

The role spans demand forecasting, pricing, search, recommendations, and segmentation, with emphasis on production discipline, CI/CD for ML, and robust