Senior Data Scientist - GSM Platform

Senior / Expert Data Scientist — Service Optimization

Location: Hà Nội - Technopark Tower/ HCM - Vincom Đồng Khởi

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About the role

GSM is building intelligent decision systems that power large-scale mobility and logistics operations. We're looking for a Senior/Expert Data Scientist to lead the development of machine learning and optimization models, plus decision-intelligence solutions across dynamic pricing, driver incentives, smart navigation, and marketplace efficiency.

This role is primarily focused on pricing and driver incentive/navigation, while also contributing to other high-impact decision problems across the organization. You'll work end-to-end — from problem framing and feature design to model development, experimentation, and measuring production impact.

We're looking for someone with strong applied-ML and analytics foundations who enjoys solving complex real-world problems using data, experimentation, and scalable machine learning.

What you'll do

Build and improve core ML models for operational decision systems

• Develop and iterate on ML solutions for dynamic pricing, dynamic driver incentive, driver smart navigation, and near-real-time demand/supply forecasting
• Design features from user behavior, driver behavior, geospatial data, and marketplace/operational signals

Drive experimentation and model improvement

• Design and execute offline and online experiments
• Define evaluation methodologies and success metrics
• Conduct root-cause analysis and model diagnostics
• Identify opportunities to improve model quality, stability, and business impact

Research and apply advanced ML techniques

• Apply modern approaches including gradient boosting (XGBoost, LightGBM, CatBoost), ranking & optimization methods, scoring & recommendation techniques, and spatio-temporal modeling
• Explore new approaches through rapid prototyping and data-driven validation

Partner across functions

• Collaborate with Product, Operations, Engineering, and Analytics to turn business challenges into measurable ML solutions
• Work closely with ML Engineers to productionize models and monitor performance
• Communicate insights, trade-offs, and recommendations to stakeholders

Own the end-to-end Data Science lifecycle

• Problem framing → data exploration → feature engineering → model development → offline evaluation → experimentation (A/B and switchback testing) → production monitoring and iteration

What you bring

Required

• Strong background in Data Science, Machine Learning, Statistics, Computer Science, Mathematics, or a related field
• 4+ years building and deploying machine learning solutions in production
• Strong Python and SQL skills
• Solid understanding of supervised learning, feature engineering, model validation, and experimentation (A/B / switchback testing)
• Hands-on experience with XGBoost, LightGBM, CatBoost or similar; large-scale structured/tabular datasets; and model evaluation & performance analysis
• Strong analytical and problem-solving skills; ability to translate business objectives into measurable ML outcomes

Strong plus

• Experience with recommendation systems, optimization systems, or ranking & scoring systems
• Marketplace, mobility, logistics, or delivery product experience
• Familiarity with geospatial modeling and time-series forecasting
• Experience designing online experiments and measuring causal impact
• Strong Kaggle profile or competitive ML experience

Nice to have

• Real-time decision systems, streaming/event-driven data
• PySpark, feature stores, or ML platform tooling
• Publications, technical blogs, open-source contributions, or competition achievements

What we value

• Strong ownership and curiosity
• Data-driven decision making
• Pragmatic problem solving
• Balancing model sophistication with business impact
• Passion for building ML systems that operate at real-world scale