Quick Summary
intent understanding, multi-step trip planning,memory, and tool calls into Agodaʼs search. Build the evaluation backbone: offline evaluations, LLM-as-judge calibrated againsthuman labels,
but exceptional DS/ML depth, strong product judgment,and the ability to ramp quickly are equally important. Why This Role Meaningful user impact: Help millions of travelers make better,
At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you’re ready to begin your best journey and help build travel for the world, join us.
Planning a trip can feel like a second job. Agodaʼs AI Assistant turns a loose travel idea into a personalized, actionable trip plan across hotels, flights, and activities. Weʼre hiring Lead/Principal Data Scientists to own how it understands, plans, recommends, and improves.
Youʼll join the team building Agodaʼs AI Assistant: The assistant runs on Agodaʼs live inventory of 6M+ properties, 130K+ flight routes and 300K+ activities, so your work can directly shape the options and decisions travelers see in live booking journeys. Weʼre early enough that the big design decisions are still open, and youʼll make many of them. The role suits senior data scientists and ML practitioners who want end-to-end responsibility for complex systems, where ML, product and engineering meet
Responsibilities
~1 min read- →Strong DS fundamentals: Modeling, statistics, experimentation and causal inference.
- →Hands-on experience building LLM systems: RAG, tool use, agent orchestration, context
and memory, with an evaluation-first approach. - →Problem-solving mindset: Excellent analytical and problem-solving skills, with comfort
operating in open-ended problem spaces where requirements evolve. - →Deep LLM experience is valuable: but exceptional DS/ML depth, strong product judgment,
and the ability to ramp quickly are equally important.
- Meaningful user impact: Help millions of travelers make better, more confident decisions
for trips that matter to them. - High ownership, high impact: Your work will shape a customer-facing system operating in
real travel and booking journeys. - Direct influence: Play a key role in both implementation and product direction.
Nice to Have
~1 min readAt Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person’s merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our privacy policy.
We do not accept any terms or conditions, nor do we recognize any agency’s representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.
Location & Eligibility
About this job
- Who can apply
- Singapore
- Posted
- 47 days ago
Listing Details
- Posted
- September 24, 2026
- First seen
- September 24, 2026
- Last seen
- November 10, 2026
Posting Health
- Days active
- 46
- Repost count
- 0
- Trust Level
- 31%
- Scored at
- November 10, 2026
Signal breakdown
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