Lead Data Scientist, Zalo Media

• Lead the design and development of ML models for candidate retrieval and multi-objective ranking, optimizing for user engagement, watch time, and content diversity.
• Drive end-to-end modeling cycles: problem scoping, data exploration, feature engineering, model training, evaluation, deployment, and monitoring.
• Own and improve online metrics (e.g., CTR, watch time, retention) and offline metrics (e.g., precision, recall, NDCG) through iterative experimentation.
• Collaborate with infra/backend teams to optimize real-time serving latency, model freshness, and feature pipelines.
• Mentor junior data scientists and contribute to the technical roadmap for the recommendation team.
• Stay current with the latest research in retrieval, ranking, large-scale machine learning, and recommenders, and apply relevant advances to production.

👾 What you will need

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, or related fields. PhD is a plus.
• Deep understanding of retrieval models (ANN, two-tower, DSSM) and ranking architectures (GBDT, DNNs, MMoE, DCN, etc.).
• Proficiency in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, or similar.
• Experience working with large-scale data (Spark, Hadoop) and real-time systems (online serving, A/B testing, streaming data).
• Strong analytical mindset with a product-oriented approach to modeling and metric design.
• Excellent communication skills, with experience collaborating in cross-functional teams.
Nice to Have
• Experience with short video or media platforms (e.g., TikTok, YouTube Shorts, Instagram Reels).
• Familiarity with multi-task learning, reinforcement learning, or causal inference in recommendation settings.
• Prior experience in leading teams or driving technical strategy in fast-paced environments.