Grab is one of Southeast Asia’s leading superapp that provides everyday services such as mobility, deliveries (food, packages, groceries), mobile payments and financial services to millions of Southeast Asians. Grab aims to use technology to empower its communities and elevate the quality of life for everyone.

Mission 1. Trust that you will have a safe ride Travel with confidence knowing that Grab’s top priority is your safety. From driver safety training and vehicle safety checks, to personal accident insurance coverage for all our drivers and passengers and government partnerships to promote safety, you know we have your back. 2. Take the transport option that fits your need We put freedom in your hands. The most transport options, at every price point, with comfort, speed and affordability – you can have it all at the touch of a button. 3. Let us take care of you We believe that a sustainable business is one that improves the lives of the people it touches – passengers, drivers, employees, governments and society at large.

Life at Grab is all about positive disruption – and yes, crazy days are part of that package too. Still, that’s never stopped a Grabber from having fun. In fact, it’s what keeps us motivated to shake things up further. Life as a Grabber means succeeding in a culture of passion and innovation. We are hungry to make a difference, and recognise that good decisions often come from the heart. We are humbled by our communities, and are proud to serve them with honour. We come from all over the world, united by a common goal to make life better everyday for our users. If you share our mission of Driving Southeast Asia Forward, apply to be part of the team today!

Grab's Data Science Department works on some of the most challenging and fascinating problems in transport, logistics, economics, and the space around. We apply deep learning, geospatial data mining, simulation, forecasting, scheduling, optimization, and many other advanced techniques on our huge datasets to push our business metrics to their bounds, directly and indirectly. We foster a culture where we enjoy raising the bar constantly for ourselves and others, and that strongly supports the freedom to explore and innovate. Sample of problems the Data Science Department solve - Intelligent allocation, machine/deep learning - based predictions (all sorts!), Dynamic pricing, Supply/demand forecasting and positioning, Incentives and promotions optimization, Carpooling, Shuttle and on-demand bus routing and scheduling, Multi-modal transport, Geospatial data mining, etc. We are the team that builds the platforms and tools that help the Data Scientists do their work. We organize the data to be used in experiments and modelling, provision the infrastructure to store and process it, and build tools to analyze it. We work with cutting edge and industry standard products to come up with solutions to various use cases for the different Data Science teams. If exploring present and emerging technologies to solve problems excite you, come and join the team. This position reports into the data science department Get to know the Role: • Plan, build, deploy, and maintain scalable machine learning infrastructure • Generate fit-for-purpose tools for various ML use cases • Leverage collected data for building ML models to solve business problems • Contribute to team's innovation and ensure up to date skills and knowledge The must haves: • Bachelor or Masters in Computer Science, Electrical/Computer Engineering , Operations Research or Mathematics/Statistics • 3 years of relevant experience in related fields • Use Spark and MapReduce technologies applied to machine learning • Admin experience of SQL based databases like PostgreSQL, MySQL • Development experience with NoSQL datastores like Cassandra, Redis, ElasticSearch • Familiarity with AWS based solutions like EMR, ec2, RDS, Kinesis • Familiarity with System Administration and scripting • Proficient in programming languages like Python, R. Knowledge of Java, GoLang would be a bonus • Understanding of ML algorithms such as neural networks, SVM, decision trees, boosting techniques, reinforcement learning IF YOU ARE INTERESTED, YOU MAY CLICK "WANT TO VISIT" TO APPLY. ONLY SHORTLISTED CANDIDATES WILLBE CONTACTED.