Senior Data Scientist (AI)

TL;DR

Senior Data Scientist (AI/ML): Developing end-to-end predictive and prescriptive analytic solutions for consumer buying behavior with an accent on Extreme Multilabel Classification and LLM fine-tuning. Focus on building scalable, production-ready deep learning models using PyTorch to transform POS data into actionable insights.

Location: Hybrid in Kuala Lumpur, Malaysia

Company

World's leading consumer intelligence company delivering a holistic view of consumer buying behavior via advanced analytics and state-of-the-art platforms.

What you will do

• Build scalable, production-ready data science solutions utilizing Tech & Durable Point-of-Sale data.
• Research and develop product-focused solutions for the T&D business.
• Build, fine-tune, and deploy state-of-the-art neural networks for Extreme Multilabel Classification.
• Collaborate with MLEs and SREs to integrate models into live production pipelines.
• Mentor junior team members and working students as a methodological expert.
• Translate complex business problems into actionable insights through cross-functional collaboration.

Requirements

• Degree in computer science, data science, statistics, or a related field.
• 5+ years of experience in a Data Science role.
• Expertise in developing and optimizing deep learning algorithms on GPU using PyTorch.
• Experience fine-tuning LLMs (e.g., from HuggingFace) and shipping large-scale models to production.
• Strong Python skills and proficiency with tools like Jupyter, PyCharm, or VSCode.
• Professional working proficiency in English.

Nice to have

• Familiarity with scikit-learn and TensorFlow.
• Experience with software engineering best practices (version control, agile, Scrum).
• Hands-on experience with GCP and productionizing models via REST API and containerization.

Culture & Benefits

• Hybrid and flexible working environment.
• Access to latest digital technologies and ongoing training.
• Personal and professional growth opportunities.
• Employee-Assistance-Program (EAP) and LinkedIn Learning.
• Volunteer time off.