Senior Data Scientist, Growth Product
New
Remote / CanadaFull-TimeSenior
Salary151,200 - 189,000 CAD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLMachine LearningProduct AnalyticsAirflowData modelingA/B testingdbt
Requirements
- 5+ years of experience in data science, decision science, or a similar quantitative role, including experience as the primary data scientist for a product domain or function.
- Strong product analytics skills. Deep experience understanding user funnels, activation metrics, and translating product usage data into actionable growth insights.
- Excellent stakeholder management and communication skills.
- Deep expertise in experimental design and causal inference (A/B testing, non-inferiority tests, factorial designs, power analysis, and related methods).
- Strong technical skills in SQL and Python.
- Hands-on experience in data pipeline tools such as dbt and Airflow.
- Strong understanding of data visualization and analytics engineering principles.
- Ability to build and maintain multi-functional relationships with various teams across the business.
Responsibilities
- Be the dedicated data science partner to the Consolidation product team, owning the analytics and modeling that power product-led growth across onboarding, activation, and full consolidation.
- Design and analyze rigorous product experiments across the client journey, from first funding through to full asset consolidation, using A/B testing, non-inferiority tests, and other causal inference methods.
- Partner with the team's Personalization DRIs to incorporate machine learning models, such as next-best-account recommendations, into product flows.
- Develop deep product analytics to understand how clients move through the consolidation funnel and identify opportunities to accelerate that journey.
- Create and maintain data models and dashboards that monitor consolidation KPIs with a focus on data quality, accessibility, and efficiency.
- Collaborate cross-functionally with Product, Engineering, Growth, and Lifecycle Marketing to translate analytical findings into product decisions.
- Proactively identify and size growth opportunities and partner with stakeholders to get those prioritized.
- Build automation tools and pipelines that increase team efficiency and scalability.
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