Data Analyst

Opus Clip is the world's No.1 AI video agent, built for authenticity on social media.

We envision a world where everyone can authentically share their story through video, with no expertise needed. Within just 18 months of our launch, over 10 million creators and businesses have used Opus Clip to enhance their social presence.

We have raised $50 million in total funding and are fortunate to have some of the most supportive investors, including Soft Bank Vision Fund, DCM Ventures, Millennium New Horizons, Fellows Fund, AI Grant, Jason Lemkin (Saa Str), Samsung Next, GTMfund, Alumni Ventures, and many more.

Check out our latest coverage by Business Insider featuring our product and funding milestones, and our recognition as one of The Information's 50 Most Promising Startups in 2024.

Headquartered in Mountain View, we are a team of 100 passionate and experienced AI enthusiasts and video experts, driven by our core values:

• Be a Champion Team

• Prioritize Ruthlessly

• Ship fast, Quality Follows

• Obsess over customers

Be a part of this exciting journey with us!

We are looking for a Data Analyst to help make our data more useful, reliable, and accessible across the company.

You will work closely with the Data Science team and partner with Product, Customer Experience, Marketing and other business teams. A large part of your role will be understanding what these teams need, translating their questions into clear analysis or reporting, and making sure the dashboards we build are genuinely useful.

This role is a good fit for someone with a solid foundation in SQL and analytics who wants to develop stronger product judgment and business understanding. You do not need to arrive with every answer. We are looking for someone who asks thoughtful questions, learns quickly, and enjoys working with others to solve practical business problems.

Improve Dashboards and Reporting

• Review existing Superset dashboards and recurring reports to understand who uses them, what decisions they support, and where they need improvement.

• Build and maintain dashboards that give teams a clear view of product usage, customer behavior, and business performance.

• Work with stakeholders to define metrics and ensure that reporting reflects current business logic.

• Monitor important dashboards and investigate unexpected changes or data-quality issues.

• Gather feedback after dashboards are launched and continue improving them based on how teams actually use them.

Support Business and Product Analysis

• Partner with Product, Customer Experience, and other teams to understand their questions and turn them into structured analyses.

• Analyze user behavior, feature adoption, conversion, retention, and other areas of the customer journey.

• Support post-launch analysis to help teams understand whether a product change achieved its intended outcome.

• Take ownership of small-to-medium analytical projects, from clarifying the question through communicating the findings.

• Identify useful patterns or opportunities in the data and recommend areas for further investigation.

Help Build More Reliable Data Practices

• Document important metrics, dashboards, tables, business definitions, and data owners.

• Help identify outdated reporting logic and work with stakeholders to confirm how it should be updated.

• Follow and contribute to standards for naming, documentation, validation, and data quality.

• Help us understand how data is being consumed before reports, tables, or pipelines are changed.

• Escalate data-quality and pipeline issues clearly to the appropriate technical owner.

Communicate and Collaborate

• Explain findings clearly to both technical and non-technical teammates.

• Regularly gather feedback from the teams using your analysis and dashboards.

• Share progress, assumptions, and limitations openly.

• Work collaboratively across teams and across US and Asia time zones.

• 1-3 years of experience in data analytics, product analytics, business intelligence, or a related analytical role.

• Strong SQL skills and experience working with large datasets.

• Experience building dashboards or recurring reports using tools such as Superset, Tableau, Looker, or Power…