Data Science Geo Maps - Internship

Company 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.

Job Description

Get to know the team

The Data Science (Geo Vision) team at Grab focuses on improving the maps and building map-based intelligence such as localization, routing, travel time estimation, traffic forecasting, that assist various Grab services like transportation, logistics, and pricing. We extensively use Computer Vision, NLP, Information Retrieval, and Text Mining along with conventional machine learning methods on a variety of signals including images, videos, text, sensor readings, GPS probes, etc to understand our locations and road networks. We also support the development of innovative, highly scalable, models through deep research and advanced analysis so that we make our products intelligent and delight our customers. 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.

Get to know the role  

We are looking for an intern data scientist to help automate the process of map creation using data science techniques. We believe a successful candidate has at least basic modern computer vision skills and deep learning knowledge, but if you believe you have what it takes then we’d love to hear from you either way. This role is required because of the very fast pace of change in the SE-Asia environment impacting deeply the maps. In return, you will get an opportunity to grow in a very challenging environment requiring innovation and creativity.

The Day-to-Day Activities

• Develop architectures to address the emerging demands of computer vision and machine learning algorithms applied in the map making process.
• Collaborate across DS teams

Qualifications

Requirements

• Familiarity with Python and some of the following libraries: PyTorch, Tensorflow or Fast.ai; NumPy; OpenCV; scikit-learn;
• Understanding of machine learning methods for classification, regression, and clustering.
• Self-motivated learner who keeps himself up-to-date with the current state of computer vision and deep learning techniques/architectures.
• Able to communicate well in English both verbally and in written communication, as well as convey data insights and results with effective visualizations.

Learning Objectives

• A good understanding of Deep Learning, in particular with design, training, evaluation, and optimization of convolutional neural net (CNN) architectures in the context of at least one of the following: object detection, segmentation, scene classification, object tracking, OCR, etc.
• Familiarity with Azure cloud platform for deploying or maintaining ML systems 

Additional Information

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 sexual orientation, and other attributes that make each Grabber unique.