Software Engineer, Data Science (Trust & Safety)

Get to know our Team:

The User Trust 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 to understanding the tradeoffs between model complexity and deployment in production. If you’re passionate about solving complex problems with immediate real-world impact, we want you!

Get to know the Role:

As a leader in an exciting and dynamic industry that is evolving daily, we are seeking talented Engineers to join our team! You will specialize in maintaining elegant products on world-class technologies that bring our unique On-Demand Transport experience to millions of people, anytime and anywhere.The Grab engineering teams work on user-facing mobile and web apps, building delightful, performant user interfaces that our passengers use to access booking and ride information. Grab full stack engineers also provide the entire company with fully-featured web portals that support interacting with passenger, driver, and bookings data.Working on the web teams at Grab is an enriching experience given the scale that we operate at. You will get to solve interesting problems by collaborating with other Engineers, UI Designers, and Data teams. You will also pick up the software engineering practices for larger teams: code reviews, ample use of static analysis, prolific feature-flagging, semantic versioning of internal APIs, and more.

The day-to-day activities:

• Test and validate these insights via rapid experimentation and deployment
• Generate multivariate statistical models to identify latent factors, preventive and preemptive capabilities that the trust framework requires

The must haves:

• Proficient in RDBMS such as PostgresQL or MySQL; and statistical programming in languages like R, Python, Java, C++ or SAS
• Experience in ETL, feature selections, modeling, model validation and conducting data analyses using R, SQL, Python or any JVM languages
• Deep understanding and implementation experience of predictive modeling algorithms such as logistic regression, neural networks, forward propagation, decision trees and heuristic models, with familiarity dealing with trade offs between model performance and business needs
• Experience in interfacing with other teams and departments to deliver impact solutions for organisation
• 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