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OpusClip is the world's leading AI video agent for social media, used by over 10 million creators and businesses. The company has raised $50 million from top-tier investors including SoftBank Vision Fund and DCM Ventures, and is recognized as one of The Information's 50 Most Promising Startups in 2024.
You will own critical data definitions and metrics across feature adoption, weekly active usage, credit consumption, user segmentation, retention, and lifetime value. This is a hands-on role combining SQL expertise, data investigation, metric governance, and stakeholder communication.
Key responsibilities include:
**Data Quality & Metric Governance:** Validate reporting tables and dashboards against source data. Establish clear definitions, assumptions, and owners for important metrics. Develop monitoring for duplicate events, volume spikes, null values, and reporting discrepancies. Investigate tracking issues and help teams distinguish genuine behavior changes from instrumentation problems.
**Product & Business Analysis:** Conduct post-launch analyses for major features. Analyze adoption, activation, funnels, retention, and user behavior. Translate ambiguous business questions into structured analytical plans and deliver actionable recommendations to product and business stakeholders.
**Retention, LTV & Finance Analytics:** Analyze subscriber retention, monetization, and customer lifetime value. Compare user and revenue behavior across plans and segments. Partner with Finance to validate reporting logic and investigate discrepancies.
**AI Partnership:** Support data curation and measurement design for AI-powered features. Define success metrics for model-driven experiences. Analyze model quality and post-launch business impact.
Within six months, you will establish trusted metric definitions, restore reporting for key product metrics, validate critical tables, introduce proactive data-quality monitoring, and deliver analyses that inform product roadmap and experimentation decisions.
The role offers exposure to a modern data stack including BigQuery, Mixpanel, Superset, Python, Prefect, and Statsig. You'll work closely with Product, Engineering, Finance, and AI teams on a mix of product analytics, data quality, experimentation, and monetization challenges.
**Requirements:**
- Typically 3+ years of experience in data science, product analytics, decision science, or equivalent
- Advanced SQL skills: complex joins, window functions, event-level analysis, cohort analysis, query debugging
- Strong Python skills for analysis, automation, validation, and statistical work
- Experience analyzing product usage, feature adoption, funnels, retention, segmentation, or monetization
- Experience defining and governing metrics (not just using existing definitions)
- Strong data-validation instincts: checking joins, duplication, nulls, freshness, source consistency
- Experience with event data from Mixpanel or similar product analytics platforms
- Dashboard building experience with Superset, Looker, Tableau, or Power BI
- Working knowledge of experimentation, statistical inference, and causal inference limits
- Strong ownership and ability to progress with ambiguous requirements
- Clear communication and experience partnering with technical and non-technical stakeholders
**Nice to have:**
- BigQuery or cloud data warehouse experience
- Background in product-led SaaS, subscription, consumer software, creator economy, or AI products
- Subscription payments, retention, revenue, or LTV analysis experience
- Familiarity with Stripe, Apple, Google Play, PIX, or payment-platform data
- Automated data-quality monitoring or anomaly detection experience
- ML/AI team collaboration on model evaluation or online experiments
- Semantic layers, metric stores, or governed self-service analytics
- Orchestration tools: Prefect, Airflow, or dbt
- Data governance, PII protection, column-level access controls
- Using AI tools to accelerate analytical work while validating output
