Gojek - Lead Data Scientist - Search & Recommendation

About The Role

As an algorithm expert on the Search and Recommendations Platform team, you will work alongside top talent in Singapore, China, Indonesia, and India to shape the intelligence behind GoFood and GoPay systems. You will design and deploy cutting-edge search, recommendations, and monetisation models that power on-demand and financial use cases across Indonesia. In your first six months, you will play a key role in launching foundational platform capabilities and collaborating with business-facing data science teams, to drive business impact and improve user experience.

If you are passionate about applying advanced algorithms to deliver real business outcomes, this is one of the highest-leverage roles in the company.

What You Will Do

• Design and optimise hybrid lexical–semantic retrieval pipelines (e.g., BM25, dense vectors, HNSW/LSH, generative retrieval) to improve precision and recall across GoFood and GoPay surfaces.
• Build high-quality embeddings and relevance signals that capture user intent, cuisine and dish semantics, geolocation, delivery constraints, price sensitivity, and promotions.
• Develop multi-task deep ranking models that balance conversion, diversity, merchant quality, and long-term user retention, integrating real-time signals such as promotions, surge, and stock availability.
• Build personalised ranking layers and user behaviour models leveraging historical orders, preferences, and contextual features.
• Engineer recommendation algorithms using collaborative filtering, graph-based methods, and sequence models for retrieval expansion (e.g., Q2Q2I, Q2I2I, U2I), including for cold-start merchants and new dishes.
• Advance embedding quality for multi-modal data (text, images, behavioural signals) and use LLMs to enhance structured knowledge (taxonomy tagging, dish attributes, dietary labels).
• Incorporate structured metadata, taxonomy signals, and knowledge-graph features into retrieval and ranking pipelines to improve semantic understanding and consistency.

What You Will Need

• Master’s degree or higher in Computer Science, Machine Learning, NLP, CV, or a related field; strong programming skills in Python, C++, or Java.
• Hands-on experience building large-scale ranking or recommendation systems in consumer products (ecommerce, food delivery, rideshare, ads, streaming, social).
• Familiarity with LLMs and/or LLVMs. Experience integrating them into search or recommendation pipelines is a strong plus.
• Demonstrated ability to innovate with new algorithms or tools and drive measurable impact, especially making use of Large language Models (LLMs) and Large Language and Vision models (LLVMs) in search or recommendation modeling.
• Strong product intuition and ability to reason from user behavior data and traffic patterns.
• Good communication skills in English, both written and verbal. Bonus points if you can understand Bahasa Indonesia.
• Self-motivated, curious, and excited by the opportunity to build high-impact systems quickly.

About The Team

We’re a growing team of algorithm members and engineers spread across Singapore, China, Indonesia, and India. We build the core search and recommendation platform capabilities to power use cases all across the GoTo universe. Everyone on the team shares a bias towards action and a passion for deploying models and strategies to real-world problems - whether it’s improving ranking and relevance accuracy, scaling LLM-powered retrieval, or personalising customer journeys.

We believe algorithm and engine application is a team sport. We work openly, challenge ideas with curiosity, and support one another to build systems that move the business forward

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.