Lead Data Science

About Agoda

Agoda was founded in 2005 by two friends with a shared passion for travel, with the aim of making global exploration simpler and more accessible. Today, the company is part of Booking Holdings and employs more than 7,000 people from 90 countries across offices worldwide. Its platform connects travelers to hotels, holiday homes, flights, and experiences, while data and technology remain central to how the business innovates and grows.

Team Overview

The Data organization, headquartered in Bangkok, handles the company’s data needs end to end. The team’s mission is to expand data adoption across the business by building and maintaining strong data capabilities, including operational and analytical databases, queueing systems, BI tools, and data science infrastructure. The group works closely with business users, product leaders, engineers, and other stakeholders to support better decision-making, improve search performance, and help protect customers from fraud.

Role Overview

This opportunity is based in Bangkok. The company is seeking driven, adaptable data scientists to work on high-scale machine learning and big data systems that process around 600 billion events each day and generate roughly 5 billion predictions. The role involves solving complex AI and ML problems across pricing, search ranking, personalization, recommendations, promotions, and insights generation, while working within a large-scale ML environment with dozens of GPUs, more than 30,000 CPU cores, and 150 TB of memory.

What You Will Do

• Build, test, and deploy models and algorithms that improve customer experience, supplier value, business results, and infrastructure readiness.
• Analyze large datasets containing hundreds of millions of customers, more than 600 million daily user events, and pricing and supplier data to uncover insights that drive product and business improvements.
• Partner with developers and business stakeholders to deliver reliable, high-quality outcomes on a daily basis.
• Research, evaluate, and apply new ideas and methods that can create meaningful impact.

Requirements

• At least 4 years of practical experience in data science.
• Strong knowledge of AI, machine learning, deep learning, and statistics, along with hands-on coding ability using relevant open-source libraries and frameworks.
• Advanced proficiency in SQL and programming languages such as Python, PySpark, and/or Scala.
• Ability to lead work independently while also contributing effectively within a team.
• Solid communication and interpersonal skills for a multicultural workplace.

Preferred Qualifications

• A PhD or MSc in Computer Science, Operations Research, Statistics, or another quantitative discipline.
• Experience with NLP, image processing, or recommendation systems.
• Hands-on exposure to data engineering and large-scale frameworks such as Spark or Hadoop.
• Background in data science for e-commerce and/or OTA businesses.

Eligibility and Location

Applications are open to both local and international candidates. Eligible applicants may receive full visa sponsorship and relocation support. The position is located in Bangkok, and the original location metadata provided was Al Rayyan, Qatar.

Equal Opportunity

Agoda states that hiring is based on merit and qualifications, and that the company welcomes applicants from all backgrounds. Employment decisions are made without discrimination based on sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, or other protected characteristics.

Application and Hiring Notes

Your application may be retained for consideration in future openings, unless you request its removal. The company also notes that it does not accept unsolicited third-party or agency terms or representations, and if it receives speculative CVs, it may contact and hire candidates directly without any obligation to pay a recruitment fee. Candidates are asked to review the hiring process guidelines before the interview.