Lead Data Scientist - Pricing System (Fulfillment)
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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
- 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 pricing across ride-hailing, food delivery and logistics
- 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 pricing system using techniques from econometrics, causal inference 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, with 5-8 years of relevant experience
- Experience working on the core dynamic pricing engine for a ride-hailing company or other similarly dynamic domain
- Solid understanding of statistics and machine learning fundamentals, with 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.
Bonus Point if you have
- Exposure to tools like Jupyter, Git, or Docker, and familiarity with software development workflows.
- Experience working with real-time ML systems—even at a project or academic level.
- Familiarity with cloud platforms (e.g. GCP, AWS, AliCloud), or modern data stack tools.
- Contributions to open-source projects or other public showcases of your work.
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 make these decisions in real time, in 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.
About GoTo Group
GoTo is the largest digital ecosystem in Indonesia. GoTo's mission is to 'empower progress' by offering technology infrastructure and solutions that help everyone to access and thrive in the digital economy.
The GoTo ecosystem provides a wide range of services, including mobility, delivery, payments, financial services, and technology solutions for merchants. The ecosystem also provides e-commerce services through Tokopedia and banking services through its partnership with Bank Jago.
About Gojek
Gojek is Southeast Asia’s leading on-demand platform and pioneer of the multi-service ecosystem with over 2.5 million driver partners across the regions offering a wide range of services such as transportation, food delivery, logistics and more. With its mission to create impact at scale, Gojek is committed to resolving consumer problems and raising standards of living by connecting consumers to the best providers of goods and services in the market.
About GoTo Financial
GoTo Financial accelerates financial inclusion through its leading financial services and merchants solutions. Its consumer services include GoPay and GoPayLater and serve businesses of all sizes through Midtrans, Moka, GoBiz Plus, GoBiz, and Selly. With its trusted and inclusive ecosystem of products, GoTo Financial is open to new growth opportunities and aims to empower everyone to Make It Happen, Make It Together, Make It Last.
GoTo and its business units, including Gojek and GoToFinancial ("GoTo") only post job opportunities on our official channels on our respective company websites and on LinkedIn. GoTo is not liable for any job postings or job offers that did not originate from us. You should conduct your own due diligence to prevent being victims of any fake job scams, if they did not originate from GoTo's official recruitment channels.
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