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SeniorFull-timeMachine LearningData ScienceML
Salary Range
$75,582 - $102,258 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Senior Principal Data Scientist to join the Fulfilment team at Grab. This role focuses on developing strategic optimization initiatives that elevate pricing, dispatch, and supply management strategies. You will combine in-depth data-driven methodologies with a strategic mindset to drive automation and marketplace efficiency.
Key Responsibilities
- →Develop ML and DL models to improve generalisation and operational efficiency
- →Create unified Reinforcement Learning architectures that coordinate multiple elements, including pricing, dispatch, and supply positioning, while balancing diverse marketplace objectives.
- →Design frameworks for joint optimization of marketplace systems through hierarchical or multi-agent RL approaches that push the operational Pareto frontier.
- →Explore representations of data that consider supply-demand signals, behaviour elasticity, and factors like weather, traffic, and user intent.
- →Build interpretable models to capture passenger and driver decision-making across diverse scenarios and operational conditions.
- →Devise feedback loops to respond to passenger and driver behaviour, considering geographical differences and behavioural patterns over time.
- →Collaborate with data engineers and backend teams to refine and integrate optimization models into real-time production systems.
- →Work with the platform and experimentation teams to validate models in live environments and drive iterative improvements.
- →Guide technical teams by leading efforts in data science while fostering collaboration and excellence.
Requirements
- ✓PhD or Master's degree in Computer Science, Statistics, Mathematics, or a related field
- ✓10+ years of experience in data science, machine learning, or a related field
- ✓Strong expertise in machine learning, deep learning, and reinforcement learning
- ✓Experience with operations research and optimization techniques
- ✓Proficiency in Python, SQL, and cloud platforms like AWS
- ✓Strong problem-solving skills and a strategic mindset
- ✓Excellent communication and collaboration skills
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