Get to know our Team:
Grab’s Data Scientists work on some of the most challenging and fascinating problems in transport, economics, logistics, and the space around. We apply machine learning, simulation, forecasting, scheduling, optimization, and many other advanced techniques on our huge datasets to push our business metrics to their bounds, directly and indirectly. 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:
- Build, validate, test, and deploy data science models to forecast and optimize operations and network efficiency across multiple verticals (transport, food, etc.)
- Design incentives and supply positioning algorithms to drive value and growth.
The day-to-day activities:
- Develop novel models and algorithms by employing operations research / machine learning / statistics / probability / economics techniques
- Contribute to team’s innovation and IP creation
- Collaborate with other data scientists, software engineers, and business operation teams
The must haves:
- Ph.D. graduate in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Electrical/Computer Engineering
- Understanding of optimization, statistics, probability, economics, algorithms
- Proficient in one or more of the following programming languages: Python, R, Scala, Matlab
- Experience with one or more big data processing frameworks such as Spark is a plus
- Experience with optimization solvers such as CPLEX / Gurobi is a plus
- Self-motivated, independent learner, and willing to share knowledge with team members
- Detail-oriented and efficient time manager in a dynamic working environment
