[Streaming] Senior Data Scientist

On behalf of our client—a leading high-traffic live-streaming and interactive video entertainment platform—we are seeking an experienced Data Scientist to join their core data science team. Operating with a mission to democratize data across the enterprise, the data team empowers internal stakeholders to seamlessly access, interpret, and derive valuable business insights from massive event-based datasets.

What you’ll do

• Custom Recommender & Growth Models: Leverage state-of-the-art algorithms to architect, train, and deploy fully customized recommendation systems and product growth models.

• End-to-End MLOps Pipeline: Design, deploy, and maintain robust end-to-end machine learning infrastructure—including feature engineering pipelines, automated model retraining/tuning workflows, and core engineering toolchains.

• Performance Monitoring & Analytics: Build comprehensive model monitoring frameworks to track real-time model health, evaluate performance, and extract actionable insights focused on user acquisition, conversion, and transactional growth.

• Cross-Functional Solution Design: Partner closely with business and product stakeholders to translate ambiguous business requirements into practical, robust, and scalable AI/ML solutions.

• Engineering & Platform Alignment: Collaborate tightly with data and backend engineering teams to ensure low-latency, scalable production deployments, driving continuous system optimization and engineering excellence.

What you’ll bring

• Core Domain Expertise: 3+ years of hands-on experience in at least one of the following domains: recommendation systems, search engines, digital advertising, content understanding/moderation, or anti-fraud systems.

• Programming & ML Stack:

  • Proficient in Python and the data science ecosystem (e.g., Pandas, NumPy, Matplotlib, Scikit-learn).

  • Expertise in at least one modern Deep Learning framework (e.g., PyTorch, TensorFlow, Keras).

  • Strong theoretical foundation in machine learning algorithms, statistical intuition, and software engineering lifecycle best practices.

• Big Data & Infrastructure: Familiarity with big data processing frameworks and tools (e.g., Spark, Ray, Hive SQL, or MapReduce).

• Communication & Mindset: Excellent communication skills with a strong track record of cross-functional collaboration. Highly curious, self-motivated, and eager to tackle technical innovation in a fast-moving environment.

• Preferred Qualifications:

  • Prior experience with large-scale recommendation models (e.g., DLRM, BERT4Rec, NCF).

  • Hands-on experience developing/deploying API services, working with GCP, and containerization technologies (Docker/Kubernetes).

  • Experience building LLM applications or working with foundational models (e.g., LLaMA, GPT) and AI tools (e.g., LangChain, Weights & Biases).

What sets this company apart

• Massive Event-Based Datasets: Direct access to rich, high-concurrency user event streams and petabyte-scale data in a dynamic digital entertainment ecosystem.

• High Impact & Real Production Ownership: Build fully customized recommendation models that directly touch millions of active users and immediately impact business conversion and revenue.

• Modern AI/ML Stack & Culture: Work in an engineering-first environment that actively encourages technical experimentation, from modern MLOps pipelines to cutting-edge GenAI/LLM application development.

What’s next

If you are a Data Scientist passionate about recommendation systems, MLOps, and leveraging quantitative models to drive product growth at scale, we would love to connect. Please submit your updated English CV to our recruitment team to initiate a confidential discussion regarding this role.