Data Scientist II

We are seeking an exceptional Data Scientist II to join our Machine Learning and Data Science team, with a focus on supporting and shaping content strategy through rigorous statistical analysis, traditional machine learning, and predictive modeling. This role will partner closely with Data Scientists, Machine Learning Engineers, content strategists, product leaders, and business stakeholders to develop models and insights that inform how we understand audiences, evaluate content performance, forecast outcomes, and optimize decision-making across the content lifecycle. We are considering applicants for the location of Los Angeles, CA or San Francisco, CA.

The ideal candidate will have experience in traditional machine learning methods, strong statistical foundations, and hands-on experience working with large-scale behavioral and content datasets. Key areas of focus will include user clustering and segmentation, behavioral modeling, content performance analysis, time series forecasting, audience engagement prediction, and KPI forecasting across acquisition, viewership, retention, monetization, and lifecycle outcomes.

This is a cross-functional role for someone who is both technically rigorous and commercially curious. Success in this position requires strong judgment in model selection, feature engineering, validation, experimentation, and interpretation, as well as the ability to communicate complex findings to both technical and non-technical audiences. The right candidate will bring a strong command of machine learning fundamentals and a passion for using data to better understand users, content, and the dynamics that drive long-term engagement.

What You Will Do:

• Develop and implement machine learning models that support content strategy, including user clustering, behavioral segmentation, engagement prediction, content affinity modeling, and audience lifecycle analysis.
• Analyze large-scale user behavior, content consumption, and performance datasets to identify patterns, trends, and opportunities that inform content investment, programming, personalization, and growth strategies.
• Apply traditional machine learning techniques such as regression, classification, clustering, dimensionality reduction, tree-based models, ensemble methods, survival analysis, uplift modeling, and time series forecasting to solve complex business problems.
• Design feature engineering, model validation, backtesting, and evaluation frameworks to ensure models are accurate, interpretable, scalable, and aligned with business objectives.
• Partner with content, finance, strategy, and engineering teams to translate ambiguous business questions into structured data science problems and actionable recommendations.
• Collaborate with Machine Learning Engineers and Data Engineers to productionize models, improve data pipelines, and ensure reliable, repeatable workflows across data science initiatives.
• Document methodologies, assumptions, experiments, model outputs, and business implications clearly to support transparency, collaboration, and stakeholder adoption.
• Stay current with advances in statistical modeling, machine learning, forecasting, behavioral analytics, and content intelligence, and natural language processing while maintaining a strong grounding in proven, interpretable modeling techniques.

We get excited about candidates, like you, because:

• You have 2+ years of experience in data science roles, preferably in technology, media, entertainment, streaming, subscription, or consumer product environments. You have demonstrated success applying data science to user behavior modeling, audience segmentation, content performance analysis, forecasting, personalization, lifecycle analytics, or related applications.
• You have a strong command of traditional machine learning methods and know when and how to apply them effectively. You are experienced with techniques such as regression, classification, clustering, dimensionality reduction, tree-based models, ensemble methods, survival analysis, uplift modeling, anomaly detection, and time series forecasting.
• You are comfortable working with large-scale behavioral, engagement, and content consumption datasets. You can identify meaningful user segments, model content affinity and engagement patterns, evaluate title or catalog performance, and translate behavioral signals into actionable insights for content, product, growth, and strategy teams.
• You are proficient in Python for data analysis and modeling, SQL for querying and transforming data, and visualization tools such as Tableau, matplotlib, or similar platforms. You have hands-on experience with machine learning libraries and frameworks such as scikit-learn, XGBoost, LightGBM, statsmodels, PyTorch, or similar tools.
• You have experience building, validating, and communicating predictive models for business outcomes such as viewership, acquisition, retention, engagement, churn, monetization, or content ROI. You understand model evaluation, backtesting, feature engineering, interpretability, and the importance of aligning technical metrics with business goals.
• You are adept at presenting complex analytical and machine learning findings in clear, actionable formats for both technical and non-technical audiences. You can explain methodology, assumptions, model outputs, tradeoffs, and business implications through concise narratives, dashboards, reports, and visualizations.
• You hold a degree in data science, statistics, computer science, economics, mathematics, engineering, or a related quantitative field. A master’s degree or advanced coursework in machine learning, statistics, econometrics, behavioral science, natural language processing, or related areas is preferred.

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 that enhance the streaming experience for millions of users and stakeholder-oriented solutions that empower internal teams with actionable insights. From building personalized recommendation systems to developing innovative tools like our stakeholder-facing chatbot, we combine cutting-edge machine learning, robust data pipelines, and advanced AI to drive impact across the organization. Collaboration, creativity, and a commitment to excellence define our team’s culture as we work together to push the boundaries of what’s possible in streaming and data-driven decision-making.

In addition to getting to work with fun, passionate and inspired colleagues, you will also enjoy the following benefits and perks:

• Receive a great compensation package including salary plus performance bonus earning potential, paid annually.
• Flexible time off policies allowing you to take the time you need to be your whole self.
• Generous medical, dental, vision, STD, LTD, and life insurance
• Health Saving Account HSA program
• Health care and dependent care FSA
• 401(k) plan, with employer match
• Employer paid commuter benefit
• Support program for new parents
• Pet insurance and some of our offices are pet friendly!

#LifeAtCrunchyroll #LI-Hybrid