Data Scientist

Angel is changing the future of entertainment and is one of the fastest-growing distributors. Our rapidly expanding library of light-amplifying stories has grown 10x in under 2 years. Gone is the old model where the deepest pockets pick the stories we share. Angel restores choice to our 2 million guild members who decide what we produce, what we take to theaters, and most importantly what parents bring to their homes. Check out angel.com/watch

You'll take ownership of how we understand user engagement and behavior, build predictive models, and create the data foundation that powers personalized discovery for millions of members. From recommendation systems to the metrics that drive our strategy, you'll turn data into insights and insights into action—shaping how fans discover and fall in love with Angel's ever-growing library of stories.

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

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

Work environmentRemote team members must have a private and quiet area for working hours in their location. When in the main office, expect a comfortable, air-conditioned work environment. Team members are issued their own desks, but the office is an open, shared space and can be fast-paced and occasionally noisy.Physical demandsWill need to be able to sit or stand at a desk for extended periods of time.Position type and expected hours of workRegular full-time, 40 hours per week.Travel required2-4 onsite events in Utah each year.

There may be other opportunities to travel, but no other significant out-of-state travel is anticipatedWork authorizationMust be authorized to work in the United States.EEO statementAt Angel Studios, we are committed to providing an environment of mutual respect where equal employment opportunities are available to all applicants and teammates.Other dutiesPlease note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the team member for this job. Duties, responsibilities and activities may change at any time with or without notice.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.