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 TIS data science team builds AI models and systems to fight fraud and risk. We extensively use data mining, machine learning, language processing and computer vision technologies on multimodality dataset of users’ whole lifecycle.
With the growth of Grab’s business and tremendous amount of activities and transactions happening hourly on the platform, there is huge demand for AI technology and great opportunity for innovation.
What You Will Do
- Work on real world challenging problems in machine learning and deep learning that can ultimately scale up the AI capability of Grab’s fraud platform.
- Assist lead data scientists in scoping, developing and evaluating fraud models.
- Develop algorithms and models, finetune and productize models.
- Explore new methodologies for fraud detection from papers and research materials.
- Documenting, presenting and communicating results to business and engineering teams.
The Day-to-Day Activities:
- Work with domain experts who understand fraud and financial risk very well.
- Mentored by lead data scientists who are experienced in respective technical domains.
- Opportunities to work with peta scale data and modern AI infrastructure.
- Open for academic research and publication.
- Learn about the exciting world of fraudsters and how to think like one (for a good cause).
Required Skills and Abilities
- Third of final year undergraduate student with good research and coding skills, Ph.D. or Master’s in CS, EE, Math or related field preferred but not a must.
- Solid machine learning theory and engineering background.
- Proficient in SQL and one of the following programming languages - Python, Julia.
- Experienced in machine learning and/or language processing.
- Current knowledge of the latest development in machine learning and deep learning.
- Hands-on experience using modern deep learning frameworks (e.g. TensorFlow, PyTorch).
- Good written and oral communication skills.
- Job type:Internships
Computer Science, Mathematics
- Closing Date:15th Jul 2022, 6:00 pm