Senior Data Scientist - Search & Recommendation

About the Role

As a senior algorithm specialist on the Search and Recommendations Platform team, you will collaborate with top professionals across Singapore, China, Indonesia, and India to enhance the intelligence behind GoFood and GoPay platforms. Your responsibilities include designing and implementing state-of-the-art search, recommendation, and monetization models serving on-demand and financial applications across Indonesia. Within your first six months, you will contribute significantly to foundational platform features and work closely with business-focused data science teams to maximize business value and improve the user experience.

If you have a passion for utilizing sophisticated algorithms to achieve tangible business results, this role represents one of the most impactful opportunities within the company.

Key Responsibilities

• Create and refine hybrid lexical-semantic retrieval systems (such as BM25, dense vector representations, HNSW/LSH, and generative retrieval methods) to increase accuracy and recall on GoFood and GoPay interfaces.
• Develop quality embeddings and relevance features that reflect user intent, dish and cuisine semantics, geolocation, delivery requirements, price sensitivity, and promotional factors.
• Construct multi-task deep ranking models that balance conversion rates, diversity, merchant quality, and long-term user retention, incorporating real-time signals like promotions, surge pricing, and item availability.
• Design personalized ranking components and user behavior models using historical order data, preferences, and context-aware features.
• Implement recommendation algorithms leveraging collaborative filtering, graph-based techniques, and sequential models for retrieval enhancement, including strategies for cold-start merchants and new dishes.
• Improve embedding methodologies for multimodal data inputs (text, imagery, behavioral metrics) and employ Large Language Models (LLMs) to enrich structured knowledge such as taxonomy tagging, dish attributes, and diet labels.
• Integrate structured metadata, taxonomy cues, and knowledge graph attributes into retrieval and ranking workflows to boost semantic accuracy and consistency.

Required Qualifications and Skills

• Possess a Master’s degree or higher in Computer Science, Machine Learning, Natural Language Processing, Computer Vision, or a related discipline.
• Strong proficiency with programming languages such as Python, C++, or Java.
• Proven hands-on experience designing and deploying large-scale ranking or recommendation systems within consumer domains like ecommerce, food delivery, ridesharing, advertising, streaming, or social platforms.
• Familiarity with Large Language Models (LLMs) and/or Large Language and Vision Models (LLVMs), including experience integrating them into search or recommendation pipelines, is highly advantageous.
• A record of innovation in applying new algorithms or tools that generate measurable outcomes, particularly with LLMs and LLVMs in search or recommendation contexts.
• Strong product intuition and analytic capability to interpret user behavior data and traffic trends effectively.
• Excellent command of English communication skills, both written and spoken. Knowledge of Bahasa Indonesia is considered a bonus.
• Self-driven, inquisitive, and eager to rapidly develop impactful systems.

About the Team

The team comprises algorithm specialists and engineers distributed over Singapore, China, Indonesia, and India. They develop central search and recommendation platform capabilities serving multiple use cases within the GoTo ecosystem. The team culture favours proactive engagement, curiosity-driven challenges, and mutual support to build solutions that advance business objectives.

Additional Information

Artificial intelligence tools may be employed to assist in parts of the recruitment process, such as application reviews, resume analysis, or response assessments to identify potential mismatches or verify candidate information. These tools support the hiring team but do not substitute human decision-making. Final hiring choices are made by humans. Contact the company for details on data handling practices.