Lead Data Scientist - Pricing System (Fulfillment)

Singapore · 5-8 years experience · Full-time · Hybrid · Posted Oct 5, 2026

At a glance

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.

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 complex problems.
Within your first six months, you'll contribute to improving dynamic pricing systems to drive the reliability of on-demand services under varying market conditions.

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.

Bachelor’s or Master’s degree in Computer Science, Statistics, Machine Learning, or a related quantitative field.
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.

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.