Mô tả công việc
Be part of one of Southeast Asia’s most ambitious superapps — a homegrown tech company solving real-world challenges across transportation, food delivery, logistics, fintech, maps, and more. We operate with millions of transactions per day, and we’re now investing heavily in cutting-edge data science to drive our next phase of growth.
If you’re excited to shape applied AI at scale in a rapidly growing ecosystem, this is your moment.
What You’ll Do
You’ll work on high-impact, cross-functional problems that sit at the heart of our superapp ecosystem:
- Model development & deployment: Build and optimize machine learning models for pricing, dispatch optimization, search ranking, recommendations, fraud scoring, and behavioral predictions.
- Full lifecycle ownership: Drive end-to-end solutioning — from understanding the business context to experimentation, deployment, and iteration.
- Smart decisioning systems: Design data-driven frameworks to support real-time decisions and large-scale automation.
- Research and innovation: Investigate state-of-the-art techniques (e.g., reinforcement learning, causal inference, graph ML) and adapt them to real-world production settings.
- Collaborative impact: Partner with product, engineering, operations, and leadership to embed intelligence into every core business process.
Example Problems You’ll Tackle
- How can we dynamically optimize supply-demand matching in real time for ride-hailing and food delivery?
- Can we personalize restaurant or service recommendations in-app within milliseconds at scale?
- What’s the best way to score driver or merchant quality to inform incentives and visibility?
- How can we reduce fraud and fake orders through predictive modeling?
- What signals should we build for map, routing, and ETA improvements across Vietnam?
Yêu cầu công việc
- Strong technical foundation: Bachelor’s or higher in Computer Science, Statistics, Applied Math, or a related field. Master’s or PhD preferred.
- Industry experience: 3+ years building and deploying ML models in production, ideally in high-scale tech environments.
- Coding skills: Proficient in Python or similar languages for data science; solid grasp of SQL and cloud platforms (e.g., GCP, AWS).
- Deep modeling knowledge: Familiarity with a wide range of techniques (e.g., XGBoost, deep learning, recommendation systems, time series, etc.).
- Problem-solving mindset: You approach messy, ambiguous problems with structured thinking and practical creativity.
- Excellent communication: Able to explain technical ideas clearly to cross-functional stakeholders and build alignment across teams.
Bonus Points
- Experience in two-sided marketplace optimization (e.g., ride-hailing, food delivery).
- Exposure to geospatial data, map systems, or search infrastructure.
- Past work on personalization, user lifecycle, or real-time decisioning.
- Contributions to open-source projects or published research.
