Senior Applied Scientist, Personalization & Recommendations

Crunchyroll; San Francisco (CA); Hybrid; USD 205,000 - 245,000; Full time

Benefits offered by this job

Salary plus performance bonus

Flexible time off

Medical, dental, vision, STD, LTD, and

Life insurance

401(k) plan with employer match

Commuter benefit

Parental support

Pet-friendly offices

Job summary

Crunchyroll is hiring a Senior Applied Scientist for Recommendation and Personalization to lead research and build production-ready personalization solutions across video, manga, ecommerce, and lifecycle marketing.

You will own problem framing, model development, offline/online evaluation, and collaboration with ML engineers, product, analytics, and engineering to improve discovery, engagement, and long-term fan value.

Qualifications

• 5+ years of experience in applied machine learning, recommendation systems, or related area with measurable product impact.
• Strong foundations in ML, statistics, experimental design, and causal thinking.
• MS or PhD in a quantitative field or equivalent industry experience.

Responsibilities

• Lead research and development of recommendation, ranking, retrieval, and personalization methods.
• Frame business questions into scientific problems, hypotheses, and metrics.
• Design offline evaluation frameworks for recommender systems and online experimentation plans.
• Collaborate with Product, Analytics, and Engineering to define experiments and roadmap.
• Translate research into production-ready solutions on our internal recommender platform.
• Communicate findings and tradeoffs clearly to stakeholders.

Skills

Applied ML

Recommendation systems

Experimentation

Python

PyTorch

TensorFlow

SQL

Cloud ML workflows

Communication

Cross-functional collaboration

Education

MS or PhD in Computer Science, ML, Statistics, OR, Economics

Tools

Scikit-learn

XGBoost

Job description

Crunchyroll is hiring a Senior Applied Scientist for Recommendation and Personalization to lead research and build production-ready personalization solutions across video, manga, ecommerce, and lifecycle marketing.

You will own problem framing, model development, offline/online evaluation, and collaboration with ML engineers, product, analytics, and engineering to improve discovery, engagement, and long-term fan value.