Data Scientist, Discovery & Personalization

Angel; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Angel Studios is seeking a data scientist to own the Discovery metrics framework across web, mobile, and TV, build a robust analytics foundation with dbt models and data pipelines, and drive data-informed decisions for millions of members.

You will lead causal inference, A/B testing, and feature engineering toward production-ready models, while collaborating with product and engineering teams in a hybrid work setup with US-authorization required.

Qualifications

• Experience designing experiments with proper power analysis and multiple comparisons.
• Familiarity with causal inference methods and observational study techniques.
• Proficiency in SQL for data exploration and Python for analysis, modeling, and automation.
• Experience building analytical data models and data pipelines (dbt, warehouses).
• Ability to communicate complex analyses clearly to stakeholders with explicit assumptions.

Responsibilities

• Define, instrument, and maintain the Discovery metrics framework across web, mobile, and TV.
• Own the A/B testing and experimentation pipeline for Discovery surfaces.
• Decode how members discover, browse, and engage across platforms; surface actionable insights.
• Distinguish correlation from causation; design quasi-experiments when needed.
• Build and maintain dbt models, data pipelines, and analytics infrastructure.

Skills

Statistical rigor

Causal inference chops

SQL fluency

Python fluency

Experiment design

Communication

Data modeling

Tools

dbt

Snowflake/BigQuery/Redshift

GrowthBook/Optimizely

Looker/Rill

Job description

Angel Studios is seeking a data scientist to own the Discovery metrics framework across web, mobile, and TV, build a robust analytics foundation with dbt models and data pipelines, and drive data-informed decisions for millions of members.

You will lead causal inference, A/B testing, and feature engineering toward production-ready models, while collaborating with product and engineering teams in a hybrid work setup with US-authorization required.