Data Scientist

Why Join Angel

• High-Growth Company: Angel is one of the fastest-growing media companies, with record-breaking independent theatrical releases and millions of streaming users worldwide. See our recent interview with Evan Shapiro
• Massive Impact: Your work will shape how audiences experience the stories they love—and help amplify light around the globe.
• Extreme Ownership: We are a team of owners and entrepreneurs. This is your chance to operate like a startup founder inside a fast-scaling media company.
• Mission-Driven Culture: We strive to amplify light in everything we do. Join a team that deeply cares about the impact of the stories we tell.
• Future of Streaming: Help build a streaming platform that competes with giants—without playing by their rules.

What You'll Do

• As our Data Scientist, you'll turn user engagement and behavior data into insights and models that power personalized discovery for millions of members. You'll work with focused depth—protected from constant priority shifts so you can deliver high-velocity, high-impact work on recommendation systems, data foundations, and the metrics that drive our strategy.
 
• Decode user behavior at scale — analyze engagement and behavior data to understand how members discover, engage with, and respond to content across our streaming platform.
• Build and train intelligent models — develop predictive models to power recommendations, personalization, and content discovery.
• Create scalable data foundations — design and build dbt models that feed analytics tools like Rill and GrowthBook, making data accessible and actionable for the entire organization.
• Pave the path to smarter recommendations — architect and prototype approaches for future recommendation algorithms that help members find the content they'll love.
• Establish trust through metrics — define, refine, and communicate the metrics that matter, building stakeholder confidence in how we measure success and partnering with engineers and product teams to determine exactly what data we need.
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What You'll Need

• Strong analytical and statistical foundation — comfortable with model training, evaluation, and turning raw data into actionable insights, with an intuition for spotting patterns, anomalies, and knowing when something doesn't add up.
• High-velocity execution with deep focus — able to deliver impact quickly and maintain momentum on deep technical work without constant context switching, while knowing when to use sophisticated models versus simple analysis.
• Strong ownership and initiative — you spot opportunities in the data, define an approach, and drive it to completion with urgency and accountability, executing with high energy and raising the bar for everyone around you.
• Exceptional communicator — able to translate complex analyses into clear narratives that non-technical stakeholders understand and trust, working collaboratively with engineers, product managers, and designers.
• Growth-oriented and curious — you proactively seek feedback, iterate quickly based on what you learn, and are excited to push the boundaries of streaming and content discovery through data science and machine learning.
 

What Success Looks Like

• Your models and insights directly improve how members discover and engage with content.
• Teams across the organization trust and regularly use the data foundations, metrics, and tools you've built.
• Stakeholders make confident decisions based on the metrics and analysis you've established.
• Your work opens doors to new possibilities—recommendation algorithms, personalization features, and data-driven product innovations.
 

Experience

• 6+ years as a data scientist, machine learning engineer, or similar analytical role, with preference for experience in streaming, entertainment, or content discovery domains
• Proven track record of building and deploying machine learning models in production, ideally including recommendation systems or personalization algorithms
• Strong foundation in statistical analysis, data modeling, and working with large-scale user engagement and behavior data
• Exceptional ability to communicate insights effectively to both technical and non-technical stakeholders
• Familiarity with modern data tools such as dbt, data warehousing, experimentation platforms (GrowthBook, Optimizely), or BI tools (Rill, Looker)
• Domain knowledge in user engagement metrics, retention analysis, or content performance measurement is a plus