Senior Data Science Manager, Marketing
New
Remote-first position across CanadaFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- LeadershipPythonSQLData scienceR
Requirements
- 5+ years of experience in data science leadership roles, managing teams of data scientists in product or marketing analytics domains.
- Strong background in causal inference, experimentation design (A/B testing), attribution modeling, and statistical modeling.
- Proficiency in SQL and Python or R for hands-on analysis and technical contribution.
- Experience influencing product or marketing strategy through data-driven insights in consumer tech or marketplace environments.
- Proven ability to communicate complex analytical concepts to both technical and non-technical audiences.
- Experience building or scaling self-serve analytics platforms or capabilities.
- Strong leadership skills with a track record of mentoring and developing high-performing teams.
- Familiarity with AI-assisted tools (e.g., LLMs, coding copilots) to enhance productivity and analytical workflows.
- Advanced degree in a quantitative field (e.g., statistics, mathematics, computer science, economics, engineering, or related disciplines) is strongly preferred.
Responsibilities
- Lead, mentor, and grow a high-performing team of data scientists focused on marketing analytics, causal inference, and experimentation.
- Define and drive the marketing data science roadmap in partnership with cross-functional stakeholders across marketing, product, and engineering.
- Develop and deploy causal models, incremental lift analyses, and predictive LTV frameworks to optimize marketing investment decisions.
- Oversee the design and implementation of measurement frameworks, including experimentation and attribution models.
- Translate complex analytical findings into clear, actionable recommendations that influence budget allocation and growth strategy.
- Ensure the integrity, quality, and consistency of marketing data through strong governance of ETL pipelines, dashboards, and reporting systems.
- Enable self-serve analytics capabilities for cross-functional teams to improve data accessibility and decision-making speed.
- Champion adoption of data-driven insights across the organization to improve marketing efficiency and performance.
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