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Mountain View, California, United States
Hybrid
🎨 OpusClip 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 OpusClip 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 SoftBank Vision Fund, DCM Ventures, Millennium New Horizons, Fellows Fund, AI Grant, Jason Lemkin (SaaStr), 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 BI.
A good foundation in analytical thinking and basic statistics.
The ability to connect a business question to the right metrics and analysis.
Clear communication skills, including the ability to explain data to non-technical audiences.
Curiosity, attention to detail, and a willingness to question unclear or outdated definitions.
A collaborative mindset and comfort seeking feedback from different teams.
Experience working in a SaaS, B2C, or fast-growing startup environment.
Experience with product analytics tools such as Mixpanel.
Familiarity with Python or R for deeper analysis.
Exposure to experimentation or A/B-test analysis.
Experience working with Product or Marketing teams.
Interest in video creation, creator tools, or the creator economy.
In your first year, you will help us:
Establish clear owners and users for our key dashboards and recurring reports.
Improve or retire reporting that is based on outdated business logic.
Give Product and Marketing teams more consistent analytical support.
Deliver useful analyses that influence product or business decisions.
Improve documentation and visibility around key metrics and data sources.
Build stronger feedback loops between the Data team and the teams using our data.
EEO
OpusClip is proud to be an equal opportunity employer. We do not discriminate in hiring or any employment decision based on race, color, religion, national origin, age, sex (including pregnancy, childbirth, or related medical conditions), marital status, ancestry, physical or mental disability, genetic information, veteran status, gender identity or expression, sexual orientation, or other applicable legally protected characteristics. OpusClip considers qualified applicants with criminal histories, consistent with applicable federal, state and local law. Opus Clip is also committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures.