Data Scientist

Join a global market leader in the live-streaming industry with over 450 million registered users. Our B2C platform leverages high-quality video technology to allow creators worldwide to monetize their talents and engage with fans in real-time. We are a fast-growing team of over 500 employees dedicated to pushing the limits of technology to remain the industry leader.

Role Overview

We are looking for a Senior Data Scientist to design and implement sophisticated ML and AI models that drive business outcomes across domains like recommendation systems, image recognition, and generative AI. You will own the entire machine learning lifecycle and collaborate with cross-functional teams to turn complex data into actionable product opportunities.

Key Responsibilities

• Model Development: Design, implement, and improve ML and AI models for recommendation systems, image recognition, and ChatBots.
• End-to-End Lifecycle: Own the full ML lifecycle, including data preprocessing, feature engineering, model training, validation, and deployment.
• Evaluation Pipelines: Build expert-level evaluation pipelines to ensure model performance, scalability, and consistency.
• Generative AI: Leverage LLMs and generative AI to enhance workflows and explore new product features.
• Collaboration: Partner with Product, Engineering, and Analytics teams to align modeling efforts with business requirements.
• Communication: Translate complex findings and model insights into clear communications for stakeholders.
  
  

• Education: BSc or higher in Computer Science, Mathematics, Statistics, or a related field.
• Experience: 4+ years of hands-on experience as a Data Scientist, preferably within the mobile, gaming, or social network industries.
• Technical Skills: Proven experience with AI/ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or LangChain.
• MLOps: Familiarity with model versioning, experiment tracking, and continuous deployment best practices.
• ML Techniques: Strong knowledge of classification, regression, segmentation, reranking, and model interpretability.
• Data & Statistics: Solid background in data analysis and the ability to design experiments and interpret results.
• Cloud Infrastructure: Experience working in cloud environments, specifically Google Cloud Platform (GCP), including BigQuery, GCS, and Vertex AI.
• Mindset: Comfortable in fast-paced, production-critical environments with a strong sense of ownership.
  
  

• Experience developing recommendation engines using deep learning and reranking techniques.
• Experience with LLM-based applications, including prompt engineering and agent development.