Job Description

Get to know Grab: Grab is more than just Southeast Asia's leading ride-hailing and mobile payments platform. We use data and technology to improve everything from transportation, Food to payments and financial services across a region of more than 62 Get to know Grab: Grab is more than just Southeast Asia's leading ride-hailing and mobile payments platform. We use data and technology to improve everything from transportation, Food to payments and financial services across a region of more than 620 million people. We work with governments, drivers, passengers, merchants, and the community, to solve critical problems in Southeast Asia. Grab began as a taxi-hailing app in 2012 but has expanded its product platform as an everyday super app in Southeast Asia. If you share our vision of driving South East Asia forward, apply to join our team today. Get to know our team: Grab's Growth Data Science Department works on some of the most challenging and fascinating problems in Transport, Food, Fintech, logistics, economics, and the space around. We apply Machine Learning, geospatial data mining, Advanced measurement methods, forecasting, optimisation, and many other advanced techniques to our massive datasets across Rides, Food and Fintech business to impact our business metrics. In addition, we foster a culture where we constantly enjoy raising the bar for ourselves and others, which strongly supports the freedom to explore and innovate. Sample of problems the Marketing Data Science Department solve - Complex Customer Lifecycle (Spread across Temporal behaviour, RFM, Geo-Spatial, User Level Persona) Recommender Systems, machine learning - based predictions, all sorts of proactive and reactive churn models, Customer LifeTime Value (CLTV), Supply/demand forecasting for cross-pollinating market places, Incentives and promotions optimisation, etc. Our team identifies and solves real-time and large-scale Marketplace Marketing problems using multiple Data Science techniques. We build, validate, test, and deploy models and algorithms using proven and experimentation techniques. We are looking for scientists who are passionate about data and want to apply advanced AI/ML techniques to solve real-world problems. This position reports to the Marketing data science department. Get to know the role: Conceptualise and develop end to end Customer lifecycle and performance marketing framework across The Grab platform ecosystem Conceptualise data model framework and architecture to address core marketing challenges across channels. The Scope of work includes overall Owned media and Paid media channels, ecosystems like Google, Facebook, Tiktok, Affiliates, Push, App-Inbox, Email, Social, Robocall, Chatbot, and Customer service channels. Incorporate measurement frameworks to analyse, Impression, ROI, CAC, Retention, and predict customer behaviour with commercial impact. Drive Customer engagement, product improvements and confidence using advanced data science techniques Develop and execute necessary analyses or A/B tests to validate Experiments and models, and perform detailed analysis to identify improvement opportunities Deep dive into data to conduct Business Insights, advanced statistical analysis and incorporate machine learning and optimisation algorithms and simulate their impact on the overall system. Effectively conceptualise analyses and present across business stakeholders and country marketing teams. Work independently or in a team to solve complex problem statements. Manage a small team of engineers, Analysts, and third-party partners for multiple concurrent projects and support them to achieve success. Communicate problem formulation, solution, analyses and insights to team members and stakeholders Build, validate, test, and deploy models and algorithms using proven and experimental techniques. Define hypotheses, develop and execute necessary tests, experiments, and analyses to prove or disprove them The must-haves: Bachelor, or Masters, Degree in Mathematics, Operations Research, Economics, Data Science, Industrial / Systems Engineering, or Computer Science, with specialisation in dealing with large data sets, User Behaviour or Optimization techniques Minimum 5-7 years of relevant post-degree experience in solving large-scale complex problems, especially in App-Based, Online Marketplaces, transport or logistics business. Proficient in Big Data Architecture and frameworks. Solid understanding of ETL pipeline, SQL, and programming languages like R and Python Knowledge of computing platforms like Spark, Airflow, and Presto/Trino on multi-cloud environments like Azure, AWS, and GC will be helpful for this role. Development experience of Visualisation tools like Tableau, Power BI, Datorama or open source visualiser, e.g. R Shiny. Experience in working with Digital/Mobile Marketplaces marketing with Customer lifecycle data, geospatial and mobility data Self-motivated, independent learner, and enjoy sharing knowledge with team members Detail-oriented and efficient time manager in a dynamic and fast-paced working environment Develop and execute necessary tests and analyses to validate models and perform detailed analysis to flag vulnerabilities and improvement opportunities Able to present complex subjects clearly and coherently to non-domain experts Detail-oriented and efficient time manager who thrives in a dynamic and fast-paced working environment