GoTo Group
Senior Manager Data Scientist - Pricing
- Employment type
- Other
- Workplace type
- Hybrid
- Location
- Singapore
- Last checked
- Oct 26, 2026
About this role
About the Role
As a Data Scientist on the Fulfilment team at Gojek, you’ll join a cross-functional group spanning Singapore, India, and Indonesia, working together to solve some of the company’s most complex and impactful problems. Our mission is to fulfil our users' orders efficiently and balance the needs of the customers, drivers and merchants.
In this role, you’ll work closely with business leaders, product managers, engineers, and fellow data scientists who are deeply committed to building real-world solutions. Within your first six months, you’ll contribute to improving our dynamic pricing systems to drive reliability of our on demand services under varying market conditions.
This is a high-impact role where core data science work directly shapes the user experience and driver earnings. If you're passionate about using data to solve real problems, thrive in a fast-moving environment, and want to see your work make a tangible difference at scale, this is the team for you.
What You Will Do
What You Will Need
Bonus Point if you have
About the Team
The fulfilment team works on some of the most high-leverage problems in Gojek. Our real time engines power all of Gojek's on demand services - food delivery, ride-hailing and logistics - and ensure the timely fulfilment of millions of orders daily.
We tackle complex, real-world challenges: What’s the best driver incentive scheme given budget and supply targets? How can pricing be adjusted to maximize revenue as well as balance customer demand and driver earnings? Why are drivers with certain characteristics more likely to complete long-distance trips than others? How long will a certain food order take for a restaurant to prepare and accordingly when should we dispatch a driver? And how do we take these decisions in real time, just a few milliseconds?
Solving these problems requires not just data and models, but thoughtful product design, experimentation, and scale. We’re equipped with rich datasets, strong cross-functional partnerships, and modern MLOps infrastructure to build and deploy impactful solutions efficiently.