About The Role

OpusClip is looking for a product-oriented Data Scientist to help us build trusted metrics, improve data quality, and turn complex product and customer data into clear business decisions.

In this role, you will own critical definitions across feature adoption, weekly active usage, credit consumption, user segmentation, retention, and lifetime value. You will validate reporting data against its source, investigate data-quality issues, and lead analyses that help Product, Finance, and AI teams understand what is working, what is not, and where we should invest next.

This is a hands-on role for someone who is equally comfortable writing SQL, investigating unexpected data, defining metrics with stakeholders, and communicating a clear recommendation.

What You’ll Do

Strengthen data quality and metric governance

• Validate reporting tables and dashboards against their source data.
• Establish clear definitions, assumptions, sources, and owners for important metrics.
• Develop monitoring for duplicate events, unexpected volume spikes, null values, stale data, and reporting discrepancies.
• Investigate tracking and data-quality issues across product events and downstream reporting tables.
• Help teams distinguish genuine changes in user behavior from instrumentation or pipeline problems.
• 
  

Lead product and business analysis

• Conduct post-launch analyses for major product features and workflows.
• Analyze adoption, activation, funnels, retention, segmentation, and user behavior.
• Translate ambiguous business questions into structured analytical plans.
• Turn findings into actionable recommendations for product and business stakeholders.
• Support our data analyst with complex or high-priority analytical requests.

About The Role

OpusClip is looking for a product-oriented Data Scientist to help us build trusted metrics, improve data quality, and turn complex product and customer data into clear business decisions.

In this role, you will own critical definitions across feature adoption, weekly active usage, credit consumption, user segmentation, retention, and lifetime value. You will validate reporting data against its source, investigate data-quality issues, and lead analyses that help Product, Finance, and AI teams understand what is working, what is not, and where we should invest next.

This is a hands-on role for someone who is equally comfortable writing SQL, investigating unexpected data, defining metrics with stakeholders, and communicating a clear recommendation.

What You’ll Do

Strengthen data quality and metric governance

• Validate reporting tables and dashboards against their source data.
• Establish clear definitions, assumptions, sources, and owners for important metrics.
• Develop monitoring for duplicate events, unexpected volume spikes, null values, stale data, and reporting discrepancies.
• Investigate tracking and data-quality issues across product events and downstream reporting tables.
• Help teams distinguish genuine changes in user behavior from instrumentation or pipeline problems.
• 
  

Lead product and business analysis

• Conduct post-launch analyses for major product features and workflows.
• Analyze adoption, activation, funnels, retention, segmentation, and user behavior.
• Translate ambiguous business questions into structured analytical plans.
• Turn findings into actionable recommendations for product and business stakeholders.
• Support our data analyst with complex or high-priority analytical requests.