Data Scientist

opusclip; Burnaby; On-site; CAD 90,000 - 130,000; Full time

Job summary

OpusClip is hiring a data scientist to own critical metrics, data quality, and business decisions. You will validate reporting, define metric ownership, and lead analyses across product, finance, and AI teams. Strong SQL and Python skills, plus experience with event data, dashboards, and monetization are essential.

Join a product-led SaaS environment in Burnaby, Canada, focusing on metric governance, segmentation, retention, and LTV to drive strategic investments.

Qualifications

• 3+ years of experience in data science, product analytics, or related field.
• Advanced SQL skills with complex joins, window functions, cohort analysis.
• Strong Python skills for analysis, automation and statistics.
• Experience analyzing product usage, funnels, retention, and monetization.
• Experience defining and governing metrics, not just using them.
• Data-validation instincts: joins, duplicates, nulls, freshness, source consistency.

Responsibilities

• Strengthen data quality and metric governance; validate reporting against sources.
• Lead product and business analysis; analyze adoption, funnels, retention and user behavior.
• Support retention, LTV, and Finance analytics across plans and payments.
• Partner with AI teams on measurement design and model-driven features.

Job description

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

About the Role

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. In this role, you will own critical definitions across feature adoption, weekly active usage, credit consumption, user segmentation, retention, and lifetime value. 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.

What You'll Do

• Strengthen data quality and metric governance
  • Validate reporting tables and dashboards against their source data.
  • Establish clear definitions, assumptions, sources, and owners for important metrics.
  • 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.
  • Analyze adoption, activation, funnels, retention, segmentation, and user behavior.
  • Translate ambiguous business questions into structured analytical plans.
  • Turn findings into actionable recommendations for product and business stakeholders.
  • Support our data analyst with complex or high-priority analytical requests.
• Support retention, LTV, and Finance analytics
  • Analyze subscriber retention, monetization, and customer lifetime value.
  • Compare user and revenue behavior across plans, segments, and payment platforms.
  • Partner with Finance to validate reporting logic and investigate discrepancies.
  • 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.

We're Looking For

• 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.
• Experience analyzing product usage, feature adoption, funnels, retention, segmentation, or monetization.
• Experience defining and governing metrics, rather than only using existing definitions.
• 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.
• Working knowledge of experimentation, statistical inference, and the limits of causal conclusions.
• Strong ownership and the ability to make progress when requirements are ambiguous.
• Clear communication skills and experience partnering with both technical and non-technical stakeholders.

Nice to Have

• Experience with BigQuery or another cloud data warehouse.
• Experience in a product-led SaaS, subscription, consumer software, creator-economy, or AI product company.
• Experience analyzing subscription payments, retention, revenue