Data Scientist (TIS)

Get to know our Team:

The Trust, Identity & Safety team acts as guardians of all our users on Grab. We leverage our rich datasets to find solutions to problems ranging from safety to fraud. We’re a hands on team interested in the end to end data lifecycle: from wrangling data, building machine learning models, to understanding the tradeoffs between model complexity and deployment in production.

As a safety data scientist, you will get exposed to the most complex real-world problems: to protect our users from threats ranging from accidents to crimes. If you are passionate about creating real-world impact using technology, this is the right place for you. You will be building products and features that would be used to protect millions of families and even save lives.

Get to know the Role:

• Develop a deep behavioral understanding and intuition of our users, especially in the space of how they would violate our policies and game our systems.

• Build machine learning models to protect our users from safety risks and deliver a safer everyday to them.

• Manage and own the entire end-to-end lifecycle of designing models, working with Engineers for implementation, to maintenance and enforcement if necessary.

• Analyze data and trends. Define effective ways to monitor model performance and propose additional features and new models to enhance model when necessary.

• Interface with business & operation teams to formulate solutions & product changes informed by your findings

• Work independently or in a team to solve complex problem statements

The day-to-day activities:

• Translate behavioral intuitions into actionable, creative insights that produces heuristic or classification models to identify and take down accounts with safety issues

• Propose and implement additional safety measures while minimise the impact on accessibility and efficiency of our services

• Test and validate these insights via rapid experimentation and deployment

The must haves:

• Minimum 3 years of experience building machine learning models in production, or an advanced degree in a quantitative field with at least 1 year of experience.

• Good understanding of machine learning models, feature engineering, and other practical issues, such as overfitting.

• Solid engineering and coding skills. And the ability to write high performance code. Experience in Python Scala and other equivalent language is a plus.

• Self-motivated, independent learner, and enjoy sharing knowledge with team members.

• Detail-oriented and efficient time manager in a dynamic and fast-paced working environment.

• Experience with NLP, computer vision, telematics or IMU motion tracking is a plus.

• Experience with MapReduce, Spark and Hive is a plus.

• Good communication skills and experience managing stakeholders is a plus.