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Entry LevelFull-timeMachine LearningData ScienceAIML
Salary Range
$16,320 - $22,080 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
The Deliveries & ACE Data Science team at Grab is central to the company's delivery and omnicommerce business. We develop and implement AI/ML models to enhance user experience across Grab's food ecosystem, including meal deliveries and restaurant reservations. Our focus is on improving user satisfaction, driving growth, and optimizing platform efficiency by addressing unique challenges in delivery, demand forecasting, and personalized dining experiences.
Key Responsibilities
- →Analyze large-scale datasets (geospatial, behavioral, transactional) to uncover actionable insights about user shopping behaviors and patterns within delivery and dine-out/reserve services.
- →Use AI to forecast shopping needs, preferences, and cancellation probabilities, improving personalized recommendations and enhancing service reliability.
- →Predict spikes in delivery demand and trends in restaurant reservations using advanced machine learning models.
- →Optimize visibility strategies to match user demand with supply, ensuring efficient network performance and reducing instances of unfulfilled orders.
- →Enable smart targeting of distinct user segments to drive demand generation efforts.
- →Design, test, and deploy AI models, refining them through A/B testing and monitoring their real-time performance.
- →Work with product managers, engineers, analysts, designers, and operations teams to scale and implement impactful solutions across the platform.
- →Contribute to the advancement of the team by driving innovation and creating intellectual property in AI/ML space for deliveries and omnicommerce.
Requirements
- ✓Strong background in data science, machine learning, or a related field.
- ✓Experience with large-scale data analysis and predictive modeling.
- ✓Proficiency in AI and machine learning techniques.
- ✓Ability to collaborate effectively with cross-functional teams.
- ✓Knowledge of geospatial, behavioral, and transactional data analysis.
