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 we'll-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 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
- bachelors or masters 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.
Bonus Points
- 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.
- Experience with causal inference and econometrics techniques
- Familiarity with cloud platforms (eg GCP, AWS, AliCloud), or modern data stack tools.
- Contributions to open-source projects or other public showcases of your work.
