Data Scientist (Demand)

Get to know the Team

• In the Demand Data Science team you are at the core and center of Grab’s ride hailing and deliveries business. We are responsible for building ML models and serving them in production to support Grab’s Advertising and Marketing services.
• Our primary goals are to help consumers discover the most attractive product, to enable the most efficient marketing campaigns for our merchants/advertisers to meet their business goals, and to build a sustainable business on our platform.
• We apply machine learning, forecasting, recommendation and optimisation techniques to huge datasets in order to model how our consumers interact on our platform under different marketing strategies. We also continuously run large-scale live experiments to improve on our implementations.
• Get to know the Role
• Explore and extract insights from massive dataset of geospatial, behavioral, economic, and tens of millions of interactions of our customers on our platform across multiple business verticals (eg, Food, Mart, Transport, etc) regionally

The Day-to-Day Activities

• Implement, validate, test, and deploy data science solutions to address particular business use cases, Scope of work includes, but is not limited to, customer segmentation, customer LTV, recommendation, conversion rate prediction, rank & re-rank, demand forecasting, campaign targeting and optimisation, etc.
• Continues improvement through iterative model enhancement and A/B testing
• Collaborate with other data scientists, software engineers, and business operation teams to deliver business solutions

Qualifications

The Must-Haves

• Master's Degree graduate in Machine Learning, Statistics, Applied Mathematics, Computer Science, Economics, Operations Research, or a related field
• Understanding of machine learning, deep learning, data mining, algorithmic foundations of optimization
• Proven track record of fast learning of new data science and ML/AI technologies
• Experience with machine learning framework (scikit-learn, Spark MLlib, Tensorflow, pytorch, etc)
• Proficient in one or more of the following programming languages: Python, Scala.
• Self-motivated, independent learner, and willing to share knowledge with team members
• Detail-oriented and efficient time manage in a dynamic working environment

The Nice-to-Haves

• Experience with building recommender systems, customer segmentations, campaign targeting, Ads bidding, campaign optimisation and etc
• Experience with algorithm and model development for large scale applications
• Hands-on experience with one or more big data processing frameworks such as Spark
• Experience with applying CI/CD principles to data science projects
• Experience with real-time data processing technologies such as Flink, Kafka, etc