Job Description

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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

Grab - the leading super app in Southeast Asia - combines transport, food delivery, logistics, payments, and much more in a single platform. The Driver Experience department dedicates to delivering best-in-class products and experiences to our driver partners, to increase adoption and engagement of our services.

Our Data Science team is a long-established core group responsible for Supply Shaping. Harnessing the power of big data and advanced ML methods, we build AI products which help our driver partners work more efficiently and ensure our platform can better serve our consumers. If you are looking for an opportunity to make an impact on the lives of millions of Grab driver partners across South East Asia, then you should join our team!

Get to know the Role

As a Data Scientist, you will be responsible for the design and implementation of the innovative and effective solutions to supply shaping problems, so as to improve the overall fulfillment service quality and driver experience. We believe a successful candidate has strong technical capability, good communication skills, and good sense of teamwork and responsibility, but if you believe you have what it takes then we\xe2\x80\x99d love to hear from you either way.

The day-to-day activities

Collaborate with cross functional teams to define business problem, scope out product development, and deliver solutions

Conduct exploratory data analysis to propose improvements to existing products, and generate ideas to shape future projects

Build and maintain efficient ETL and ML pipelines to support existing team projects

Develop novel models and algorithms by employing operations research / machine learning / statistics / probability / economics techniques

Support experiment design and analysis to measure the product impacts

Contribute to team\'s innovation and IP creation

Learning Opportunities

Be mentored by senior data scientists who are experienced in respective technical domains

Utilise the tech industry\xe2\x80\x99s state-of-the-art ML tools and AI infrastructure

Opportunities to work with peta scale data

The Must-Haves

Bachelor degree in Computer Science, Electrical/Computer Engineering, Industrial & Systems Engineering, Operations Research, Mathematics/Statistics, or related technical disciplines

Solid Machine Learning fundamentals:

Good understanding of statistics and ML models

Hands-on experience in using mainstream deep learning frameworks (e.g. TensorFlow, PyTorch) preferred

Hands-on experience in forecasting models is a plus

Basic software skills:

Grab Confidential and Proprietary Owner:

Ops Excellence (Talent Acquisition) | go/jdtemplate

Proficient in one or more of the following programming languages: Python, R, Scala

Knowledge of distributed data processing frameworks will be a plus \xe2\x97\x8b Experience with cloud-based development (AWS/Azure) will be a plus

Software engineering experience (including school course projects, as long as project is significant enough and candidate has major contribution) will be a plus

Self-motivated, passionate to learn about new ML methods and big data infrastructure, and willing to share knowledge with team members

Ability to work in a dynamic and fast-paced working environment while maintaining attention to detail and efficient time management

Efficient and detail oriented time manager who thrives in a dynamic and fast-paced working environment

Excellent communication skills, ability to translate complex technical details for non-technical audiences

Our Commitment

We are committed to building diverse teams and creating an inclusive workplace that enables all Grabbers to perform at their best, regardless of nationality, ethnicity, religion, age, gender identity or sexual orientation and other attributes that make each Grabber unique.

Grab