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Senior Data Scientist (Search and Recommendations)

Grab
Singapore, UAE
Full Time
Senior
Onsite
1 months ago
PythonScalaDeep LearningMachine LearningPyTorchTensorFlow
Free

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PythonScalaDeep Learning
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Get to Know the Team

  • You will join our Search and Recommendations team — a group of machine learning engineers and data scientists who build algorithms that help millions of users discover food, groceries, and services across Southeast Asia.

Get to Know the Role

  • You will report into the Senior Data Science Manager, and work onsite at Grab One North Singapore office.
  • You will design and build machine learning systems that power search ranking and personalized recommendations at scale.

The Critical Tasks You will Perform

  • Design and implement deep learning algorithms for search ranking, session based recommendations, and multi objective personalization systems.
  • Fine tune and deploy Large Language Models (LLMs) to improve search query understanding and recommendation relevance.
  • Lead offline evaluation design and online A/B testing to validate model performance.
  • Partner with software engineers to scale your models from prototype to production.
  • Translate data insights into concrete product features by collaborating with product managers and business operations teams.
  • Monitor model performance in production and implement retraining pipelines.

What Essential Skills You will Need

  • Master's in Computer Science, Operations Research, Statistics, or equivalent quantitative field, or equivalent practical experience.
  • At least 3 years of experience building and deploying deep learning models for search, recommendation systems, or NLP applications in production environments.
  • Hands on experience with Python and Scala to build data pipelines and model serving systems.
  • Proficiency in at least one deep learning framework (PyTorch, TensorFlow, or JAX).
  • Experience with LLM fine tuning and deployment using frameworks such as Hugging Face Transformers.
  • Demonstrated experience with A/B testing frameworks and statistical evaluation methods.
  • Experience deploying models to production using ML serving infrastructure and optimising for latency constraints.

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