Data Science Lead, AI-Driven Product Analytics

OpusClip

Mountain View (CA)

On-site

USD 200,000 - 320,000

Full time

11 days ago

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Job summary

OpusClip is seeking a staff-level, product-oriented Data Science leader to build an effective and increasingly AI-native data function. You will set priorities for a small Data team and personally lead our hardest analytical problems to help product and business decisions.

This hands-on role partners with Product, Growth, Finance, Engineering, and AI to improve measurement, data quality, and self-serve analytics.

Qualifications

  • Significant experience in data science, product analytics, decision science, or a closely related field.
  • Demonstrated leadership in data teams and ability to influence without formal authority.
  • Strong product judgment and ability to identify questions that drive business outcomes.
  • Hands-on proficiency with SQL, Python, and modern analytics tooling.

Responsibilities

  • Lead the Data function, setting priorities for a small team and driving high-impact analyses.
  • Drive product and business decisions by analyzing activation, retention, segmentation, monetization, and LTV.
  • Improve data quality, standard definitions, and reliable measurement across product and business metrics.
  • Build Growth intelligence and create tools to inform acquisition, retention, CAC, and monetization.
  • Partner with AI teams to evaluate data for AI features and ensure data quality supports product experiences.

Skills

Strong SQL & Python
Product analytics
Decision science
Leadership
Data storytelling

Tools

BigQuery
Mixpanel
Superset
Python
Prefect
Airflow
dbt

Job description

OpusClip is seeking a staff-level, product-oriented Data Science leader to build an effective and increasingly AI-native data function. You will set priorities for a small Data team and personally lead our hardest analytical problems to help product and business decisions.

This hands-on role partners with Product, Growth, Finance, Engineering, and AI to improve measurement, data quality, and self-serve analytics.

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