Job Description

Life at Grab At Grab, every Grabber is guided by The Grab Way, which spells out our mission, how we believe we can achieve it, and our operating principles - the 4Hs: Heart, Hunger, Honour and Humility. These principles guide and help us make decisions as we work to create economic empowerment for the people of Southeast Asia. Get to know the Team The Growth team at Grab tackles various challenges in transportation, food, fintech, logistics, economics and more. Within the Growth team, The Growth Data Science team utilises advanced techniques such as Machine Learning, geospatial data mining, forecasting, optimization and other methods to analyse vast amounts of data across our Rides, Food, and Fintech businesses. We encourage a culture of innovation, where we continuously strive to set higher standards for ourselves and our colleagues. Our team uses machine learning-based predictions and proactive/reactive churn models to solve complex problems related to the customer lifecycle, such as temporal behaviour, RFM, geospatial analysis, and user-level persona. Get to know the Role Design and implement essential Consumer Growth Data Pipelines to create and uphold vital dashboards that are acknowledged as the primary source of truth by the management teams The Day-to-Day Activities Conduct advanced statistical analysis, incorporate machine learning, and simulate their impact on the overall platform for Business Insights. Effectively conceptualise analyses and present them across business stakeholders and country marketing teams. Work independently or in a team to solve complex problem statements. Act as a bridge between CRM, Performance Marketing, Product, Customer Experience, and Country Ops Develop and execute necessary analyses or A/B tests to validate Experiments and models and perform detailed analysis to identify improvement opportunities. 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 and execute necessary tests, experiments, and analyses to prove or disprove them. The Must-Haves Bachelor\'s or Master\'s degree in a relevant field, with a specialisation in dealing with large data sets, User Behaviour, or Optimization techniques Minimum four 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 Development experience with Visualisation tools like Power BI, Datorama, or open source visualiser, e.g. R Shiny Experience in working with Digital/Mobile marketplace marketing with Customer lifecycle data, geospatial, and mobility data Self-motivated, independent learner, and enjoys sharing knowledge with team members Detail-oriented and efficient time manager in a dynamic and fast-paced working environment Able to develop and execute necessary tests and analyses to validate models and perform detailed analyses to flag vulnerabilities and improvement opportunities Able to present complex subjects clearly and coherently to non-domain experts and Business Leaders Experience with cloud computing platforms, containerization technologies and agile development methodologies Our Commitment We recognize that with these individual attributes come different workplace challenges, and we will work with Grabbers to address them in our journey towards creating inclusion at Grab for all Grabbers. About Grab Grab is the leading superapp platform in Southeast Asia, providing everyday services that matter to consumers. Today, the Grab app has been downloaded onto millions of mobile devices, giving users access to over 9 million drivers, merchants, and agents. Grab offers a wide range of on-demand services in the region, including mobility, food, package and grocery delivery services, mobile payments, and financial services across 428 cities in eight countries.

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