Crunchyroll
Overview
Senior Data Scientist role at Crunchyroll. Location: Los Angeles, CA or San Francisco. Report to the Director of Machine Learning and Data Science. About Crunchyroll
Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We serve over 100 million anime and manga fans across 200+ countries and territories, connecting them with stories and characters through streaming video, in-person experiences, games, merchandise, and events. Join our team and help shape the future of anime. About The Role
In the role of Data Scientist, you will work with Senior Data Scientists and Machine Learning Engineers to maintain, enhance, and innovate our suite of machine learning and AI-driven models and services. The role focuses on churn and winback predictions, predictive lifetime value (LTV), financial forecasting, title- and catalog-level KPI forecasting (e.g., acquisition, viewership), high-value action analysis in subscriber lifecycle management, and user behavior modeling for fraud detection and recommendation systems. The ideal candidate will have a strong foundation in statistical and machine learning fundamentals and experience with modern data science tech stacks to drive impactful solutions for both consumer-facing and stakeholder-oriented initiatives. Core Areas of Responsibility
Develop and implement new models or enhancements to drive innovation in predictive analytics and personalized user experiences. Analyze large-scale datasets to uncover insights, identify trends, and inform model development and optimization. Apply statistical and machine learning techniques to solve complex business problems and improve model performance. Work with modern data processing tools, modeling frameworks, MLOps pipelines, and cloud infrastructure to ensure efficient and scalable workflows. Partner with cross-functional teams, including Machine Learning Engineers, AI Engineers, and Platform/Software Engineers, to integrate models into production environments. Document methodologies, experiments, and findings to support team collaboration and knowledge sharing. Stay current with advancements in data science, machine learning, and related technologies to bring cutting-edge approaches to our solutions. About You
Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. Strong understanding of statistical and machine learning fundamentals and their practical applications. Proven experience in developing and optimizing machine learning models for predictive analytics, forecasting, or recommendation systems. Proficiency in Python and familiarity with data science libraries such as pandas, NumPy, scikit-learn, statsmodels, TensorFlow, or PyTorch. Experience with modern data processing tools (e.g., Apache Spark, SQL) and cloud infrastructure and services (e.g., AWS, Google Cloud, Databricks). Familiarity with MLOps practices and tools (e.g., version control, pipelines, containerization, orchestration) for model testing, deployment and monitoring. Strong analytical and problem-solving skills with a focus on delivering actionable insights. Excellent communication and collaboration skills to work effectively with interdisciplinary teams. Pluses
Experience with churn prediction, customer lifetime value modeling, financial forecasting with time series or deep learning models, or recommendation systems in a consumer-facing industry. Knowledge of advanced statistical methods, such as Bayesian modeling or causal inference. Understanding of subscriber lifecycle management and high-value action analysis. Comfortable with imperfect and evolving data, working with “raw” data such as events, and seeking solutions to improve data qualities. About The Team
You will join an interdisciplinary team of Data Scientists, Machine Learning Engineers, and AI Engineers, united by a passion for leveraging data and ML/AI to create transformative solutions. Our team delivers both consumer-facing product features and stakeholder-oriented solutions, combining cutting-edge machine learning, robust data pipelines, and advanced AI to drive impact across the organization. Equity, Benefits and Values
Why you will love working at Crunchyroll: competitive compensation package with salary plus performance bonus, comprehensive benefits (medical, dental, vision, life insurance, HSA, FSA), 401(k) with employer match, and flexible time off. We value courage, curiosity, kaizen, and service, and are committed to diversity and inclusion. Crunchyroll is an equal opportunity employer. We do not discriminate on any protected characteristic. Questions about Crunchyroll’s hiring process? Please refer to our Hiring FAQs: https://help.crunchyroll.com/hc/en-us/articles/360040471712-Crunchyroll-Hiring-FAQs. For more information about data privacy, see our Candidate Privacy Policy: https://tbcdn.talentbrew.com/company/22978/v1_0/docs/spe-jobs-privacy-policy-update-for-crpa-dec-21-22.pdf. Please beware of scams; only messages from @crunchyroll.com email accounts are legitimate.
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Senior Data Scientist role at Crunchyroll. Location: Los Angeles, CA or San Francisco. Report to the Director of Machine Learning and Data Science. About Crunchyroll
Founded by fans, Crunchyroll delivers the art and culture of anime to a passionate community. We serve over 100 million anime and manga fans across 200+ countries and territories, connecting them with stories and characters through streaming video, in-person experiences, games, merchandise, and events. Join our team and help shape the future of anime. About The Role
In the role of Data Scientist, you will work with Senior Data Scientists and Machine Learning Engineers to maintain, enhance, and innovate our suite of machine learning and AI-driven models and services. The role focuses on churn and winback predictions, predictive lifetime value (LTV), financial forecasting, title- and catalog-level KPI forecasting (e.g., acquisition, viewership), high-value action analysis in subscriber lifecycle management, and user behavior modeling for fraud detection and recommendation systems. The ideal candidate will have a strong foundation in statistical and machine learning fundamentals and experience with modern data science tech stacks to drive impactful solutions for both consumer-facing and stakeholder-oriented initiatives. Core Areas of Responsibility
Develop and implement new models or enhancements to drive innovation in predictive analytics and personalized user experiences. Analyze large-scale datasets to uncover insights, identify trends, and inform model development and optimization. Apply statistical and machine learning techniques to solve complex business problems and improve model performance. Work with modern data processing tools, modeling frameworks, MLOps pipelines, and cloud infrastructure to ensure efficient and scalable workflows. Partner with cross-functional teams, including Machine Learning Engineers, AI Engineers, and Platform/Software Engineers, to integrate models into production environments. Document methodologies, experiments, and findings to support team collaboration and knowledge sharing. Stay current with advancements in data science, machine learning, and related technologies to bring cutting-edge approaches to our solutions. About You
Master’s degree in Data Science, Statistics, Computer Science, Mathematics, or a related field. Strong understanding of statistical and machine learning fundamentals and their practical applications. Proven experience in developing and optimizing machine learning models for predictive analytics, forecasting, or recommendation systems. Proficiency in Python and familiarity with data science libraries such as pandas, NumPy, scikit-learn, statsmodels, TensorFlow, or PyTorch. Experience with modern data processing tools (e.g., Apache Spark, SQL) and cloud infrastructure and services (e.g., AWS, Google Cloud, Databricks). Familiarity with MLOps practices and tools (e.g., version control, pipelines, containerization, orchestration) for model testing, deployment and monitoring. Strong analytical and problem-solving skills with a focus on delivering actionable insights. Excellent communication and collaboration skills to work effectively with interdisciplinary teams. Pluses
Experience with churn prediction, customer lifetime value modeling, financial forecasting with time series or deep learning models, or recommendation systems in a consumer-facing industry. Knowledge of advanced statistical methods, such as Bayesian modeling or causal inference. Understanding of subscriber lifecycle management and high-value action analysis. Comfortable with imperfect and evolving data, working with “raw” data such as events, and seeking solutions to improve data qualities. About The Team
You will join an interdisciplinary team of Data Scientists, Machine Learning Engineers, and AI Engineers, united by a passion for leveraging data and ML/AI to create transformative solutions. Our team delivers both consumer-facing product features and stakeholder-oriented solutions, combining cutting-edge machine learning, robust data pipelines, and advanced AI to drive impact across the organization. Equity, Benefits and Values
Why you will love working at Crunchyroll: competitive compensation package with salary plus performance bonus, comprehensive benefits (medical, dental, vision, life insurance, HSA, FSA), 401(k) with employer match, and flexible time off. We value courage, curiosity, kaizen, and service, and are committed to diversity and inclusion. Crunchyroll is an equal opportunity employer. We do not discriminate on any protected characteristic. Questions about Crunchyroll’s hiring process? Please refer to our Hiring FAQs: https://help.crunchyroll.com/hc/en-us/articles/360040471712-Crunchyroll-Hiring-FAQs. For more information about data privacy, see our Candidate Privacy Policy: https://tbcdn.talentbrew.com/company/22978/v1_0/docs/spe-jobs-privacy-policy-update-for-crpa-dec-21-22.pdf. Please beware of scams; only messages from @crunchyroll.com email accounts are legitimate.
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