Data Scientist - Fulltime (Vancouver)

Data Scientist - Fulltime (Vancouver)

03 Oct
|
OPUS
|
Vancouver

03 Oct

OPUS

Vancouver

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. Headquartered in Mountain View, we are a team of 100 passionate and experienced AI enthusiasts and video experts, driven by our core values: Ship fast, Quality Follows Obsess over customers 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. 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. Strengthen data quality and metric governance Validate reporting tables and dashboards against their source data. 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.

Support our data analyst with complex or high-priority analytical requests. Analyze subscriber retention,



monetization, and customer lifetime value. Communicate assumptions and data limitations clearly when working with financial and payment-related data.

Partner with our AI teams Support data curation, measurement design, and evaluation for AI-powered product experiences. Define offline and online success metrics for model-driven features. Analyze model quality, user behavior, and post-launch business impact.

Partner on experimentation, segmentation, and ongoing performance monitoring. Typically 3+ years of experience in data science, product analytics, decision science, or a closely related field—or equivalent experience owning work at this level. Advanced SQL skills, including complex joins, window functions, event-level analysis, cohort analysis, and query debugging.

Strong

Python skills for analysis, automation, validation, and statistical work. Strong data-validation instincts, including checking joins, duplication, nulls, freshness, source consistency, and tracking changes.

Experience working with event data from Mixpanel, or a similar product analytics platform.

Experience building or maintaining dashboards using tools such as Superset, Looker, Tableau, or Power BI. Clear communication skills and experience partnering with both technical and non-technical stakeholders.

Experience with BigQuery or another cloud data warehouse.

Experience in a product-led SaaS, subscription, consumer software, creator-economy, or AI product company. Familiarity with Stripe, Apple, Google Play, PIX, or other payment-platform data.





Experience with automated data-quality monitoring or anomaly detection.

Experience partnering with ML or AI teams on model evaluation, data curation, or online experiments. Exposure to orchestration and transformation tools such as Prefect, Airflow, or dbt. Awareness of data governance, PII protection, and column-level access controls.

Experience using AI tools to accelerate analytical work while independently validating the output. Validated critical reporting tables against their source data. Introduced proactive monitoring for high-impact data-quality issues.

Delivered product analyses that directly informed roadmap, launch, or experimentation decisions. Work closely with Product, Engineering, Finance, CX, and AI teams. Help shape the analytical foundation of a fast-growing AI product.

Work with a up-to-date data stack that includes BigQuery, Mixpanel, Superset, Python, Prefect, and Statsig. Tackle a mix of product analytics, data quality, experimentation, monetization, and AI evaluation. Grow toward broader ownership in product data science, experimentation, metric governance, or analytical leadership.

If you enjoy finding the truth behind the numbers—and making that truth useful to the people building the product—we’d love to hear from you. 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. #

📌 Data Scientist - Fulltime (Vancouver)
🏢 OPUS
📍 Vancouver

Reply to this offer

Impress this employer describing Your skills and abilities, fill out the form below and leave Your personal touch in the presentation letter.

Subscribe to this job alert:

Get the latest job offers by email for: data scientist - fulltime (vancouver) / vancouver