Data Scientist (ML)

The R& D team is dedicated to developing, testing, and validating robust and scalable machine learning models that drive business objectives. Our focus includes enhancing operational processes through AI/ML solutions, such as trend analysis, anomaly detection, and the deployment of large language models (LLMs) for tasks like querying system health. Another major focus area is preserving and improving customer experience and retention. We closely work with our stakeholders to ensure AI/ML objectives are clearly defined.

Responsibilities

• Lead and mentor a team of data scientists focused on developing and deploying ML solutions, including GNNs, LLM-based applications, and fraud detection models.
• Define and drive the roadmap for AI/ML initiatives across Crunchyroll's product and platform ecosystem.
• Guide the development of robust ML pipelines and infrastructure, working closely with data engineering, software engineering, and DevOps teams.
• Establish best practices for experimentation, model evaluation, A/B testing, and continuous learning in production environments.
• Work with stakeholders across business, marketing, security, and content teams to identify AI opportunities and translate them into actionable projects.
• Ensure responsible AI/ML development by emphasizing model interpretability, performance, and fairness.
• Own operational metrics around model impact, latency, cost, and system scalability.
• Foster a strong team culture centered on innovation, curiosity, collaboration, and continuous learning.

Requirements

• Bachelor's or Master's in Computer Science, Statistics, Data Science, or a related quantitative field.
• 5+ years of industry experience in data science or applied ML, with 2+ years of people leadership experience.
• Proven track record of delivering production ML systems that solve real-world business problems.
• Deep knowledge of ML/AI frameworks (e. g., PyTorch, TensorFlow, HuggingFace) and experience with applied NLP, GNNs, GraphRAG, and embeddings.
• Experience building systems leveraging Graph Databases, Vector Stores (e. g., FAISS, Pinecone), and cloud-native ML stacks (SageMaker, Databricks, etc. ).
• Strong technical leadership, with the ability to direct teams to develop optimal ML solutions and guide the research-to-production lifecycle.
• Excellent communication and stakeholder management skills; able to translate between business and technical worlds.
• A passion for building high-performing teams, mentoring others, and fostering a learning-first environment.