- Job Type: Full-Time
- Function: Data Science
- Industry: Consumer
- Post Date: 05/29/2026
- Website: www.gotocompany.com/en
- Company Address: , Jakarta, ID
About GoTo Group
GoTo is the largest technology group in Indonesia, combining on-demand and financial services through the Gojek and GoTo Financial brands. It is the first platform in Southeast Asia to host these two essential use cases in one ecosystem, capturing a majority of Indonesian consumer household expenditure.Job Description
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 driver incentives to drive reliability of our on demand services.
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.
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.
As a team, we’re concerned not only with the growth of the company, but each other’s personal and professional growths, too. Along with keeping fit (via table tennis or other activities), our team bonds over our shared love of traveling and eating.
What You Will Do
- Translate complex business challenges into well-defined technical problems solvable with data, statistics, and machine learning.
- Collaborate with product managers, engineers, and business stakeholders to build and scale data science solutions that power driver allocations, surge pricing and driver incentives.
- Own the full ML lifecycle—from ideation and research to model development, pipeline implementation, deployment, experimentation, and driving measurable business outcomes.
- Improve the efficiency of our dynamic driver incentives using techniques from machine learning, causal inference, optimization and simulation
- Design and interpret experiments to measure model impact, working with analysts and product teams to ensure rigorous evaluation and clear success metrics.
- Monitor and evaluate model performance, identifying areas for improvement and proposing solutions
- Communicate insights, trade-offs, and technical decisions effectively to cross-functional stakeholders, and operate with a high degree of autonomy in ambiguous problem spaces.
What You Will Need
- Bachelor’s or Master’s degree in Computer Science, Statistics, Machine Learning, or a related quantitative field
- Solid understanding of statistics and machine learning fundamentals, with coursework or projects demonstrating practical application.
- Proficiency in Python and SQL, and familiarity with data analysis or modeling libraries.
- Strong analytical thinking and problem-solving skills, with the ability to reason from data and communicate findings clearly.
- A willingness to learn fast, take initiative, and work collaboratively in a cross-functional team.
- Curiosity, humility, and a drive to apply data science to real-world problems at scale.