Lead Data Scientist (Dispatch)

Get to Know the Team

Grabs Fulfillment Dispatch Data Science team tackles allocation and batching challenges to ensure passengers driver-partners consumers and merchants experience reliable fulfillment Dispatch at Grab involves solving sequential decision-making problems through multi-stage optimization rather than static matching. This requires working on Reinforcement Learning (RL) Optimization Simulation and Graph Theory research and applications.

Get to Know the Role

As a Lead Data Scientist youll report into the Senior Data Science Manager and work onsite at Grab One North Singapore office. Youll build and deploy RL and optimization models that improve dispatch operations across our marketplace. Youll lead the lifecycle of our dispatch modelsfrom understanding business needs and identifying areas for investigation to translating them into technical problems and delivering solutions.

The Critical Tasks You Will Perform

• Youll analyse high-volume high-velocity data to prototype reinforcement learning and optimization models then engineer these into production-grade systems
• Youll design develop and deploy production-grade models that improve dispatch decisions and respond to changes in market conditions
• Youll build data pipelines and conduct experiments (A/B tests randomised controlled trials) to measure the real-world impact of your models
• Youll communicate technical results and their business implications to product and business stakeholders including explaining model behaviour in non-technical terms
• Youll keep current with reinforcement learning and operations research developments share knowledge with your team and the data science community at Grab and contribute to our technical competitive advantages

Qualifications :

What Essential Skills You Will Need

To perform these tasks youll need:

• Advanced degree in a technical field A PhD in Computer Science Operations Research Industrial & Systems Engineering Mathematics or related disciplines with at least 5 years of relevant experience. This equips you with the theoretical foundations needed to design complex optimization and learning algorithms.
• RL and optimization expertise Experience developing production-grade RL and Operation Research (OR) systems including feature extraction data pipelines and system maintenance. You need this to build models that make real-time dispatch decisions.
• Statistical and analytical skills Knowledge of probability and statistics (hypothesis testing modelling distributions Bayesian statistics) and experience with large-scale data analytics using Spark or Kafka. You need this to design experiments and process the massive datasets generated by our marketplace.
• Programming proficiency Fluency in Python for model development and familiarity with cloud-based development environments (AWS or Azure) and test-driven development. You need Python to implement algorithms and cloud platforms to deploy models at scale.

Additional Information :

Life at Grab

We care about your well-being at Grab here are some of the global benefits we offer:

• We have your back with Term Life Insurance and comprehensive Medical Insurance.
• With GrabFlex create a benefits package that suits your needs and aspirations.
• Celebrate moments that matter in life with loved ones through Parental and Birthday leave and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
• We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through lifes challenges.
• Balancing personal commitments and lifes demands are made easier with our FlexWork arrangements such as differentiated hours

What We Stand For at Grab

We are committed to building an inclusive and equitable workplace that enables diverse Grabbers to grow and perform at their best. As an equal opportunity employer we consider all candidates fairly and equally regardless of nationality ethnicity religion age gender identity sexual orientation family commitments physical and mental impairments or disabilities and other attributes that make them unique.

Remote Work :

No

Employment Type :

Full-time