Senior Lead, Data Science & Machine Learning

Job De ion

Job ID: MJ000276

About Traveloka

Traveloka is Southeast Asia's leading travel and lifestyle super-app. We connect tens of millions of travellers across the region with flights, hotels, experiences, financial services, and more - all from a single platform. Since our founding in 2012, we have expanded to eleven markets, processed billions of dollars in transactions, and built one of the most recognised consumer brands in the region.

We move fast because the region demands it. Southeast Asia is young, mobile-first, and growing faster than almost anywhere else on earth. We are not transplanting a Western playbook - we are writing a new one, from scratch, for a market that does not look like anywhere else - and we are calling for people who want to be part of that.

About The Team

Discovery is how millions of travellers across Southeast Asia find their next trip - the search, ranking, and recommendations that turn a vague idea into a booked flight, hotel, or experience. Data science builds the models and data foundations behind that moment, and you would sit at its core: the experimentation, machine learning, and business intelligence that make discovery smarter every release.

Here you work on relevance and personalisation at genuine scale, across 11 markets, many languages, and travel patterns no Western playbook anticipated. You turn raw signals into features, models, and metrics that ship - not dashboards that sit unread. If you want your data science to move what real users see and book, this is where it lands.

About The Job

As a Senior Lead Data Scientist, you are the most senior individual contributor across the end-to-end user journey, from discovery and ranking to pricing. You set the technical direction for the hardest problems and deliver the breakthrough work yourself, carrying decision authority on short-term technical questions across the domain without managing a team.

Set the modelling and experimentation direction across the product funnel and personally lead the highest-stakes problems

Architect systems that hold up at the scale of millions of bookings and a global user base, owning the hard trade-offs

Make the call on contentious short-term technical questions, from metric definitions to model architecture, across the domain

Resolve the measurement and modelling problems that block whole teams, and define the patterns they then reuse

Influence product and business strategy with a data-science perspective leaders trust

Find where existing models, pipelines, or metrics quietly cost the business at scale, and drive the fix

Mentor senior scientists and raise the technical bar across the domain through review and example

Job Requirements

You have at least 10 years of relevant experience.

You have the deepest technical command of Python and the ML/stats stack (scikit-learn, LightGBM, XGBoost, deep learning and optimisation where relevant)

You write advanced SQL and architect the large-scale data and feature systems whole teams rely on

You take the most ambiguous, domain-spanning problems and turn them into the bets the funnel is organised around

You have authoritative command of search, recommendation, ranking, and pricing systems at marketplace scale

You understand marketplace economics deeply and anticipate the second- and third-order effects of a model change

You design and adjudicate sophisticated experimentation and own the measurement standard others defer to

You set technical direction across teams through influence, judgment, and decision authority on the issues in your remit

You hold a degree in a quantitative field (Master's or higher preferred) or equivalent, and influence senior cross-functional leaders

You work confidently with cloud (GCP preferred) and production ML, and set the bar for AI-assisted ways of working

You have a track record of models that delivered large, attributable business impact at marketplace scale

You have designed an internal ML platform, feature store, or experimentation framework that changed how teams build

You have worked on marketing or commercial measurement (MMM, MTA, propensity, CLV) that informed real spend or pricing decisions

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