Staff Data Scientist, Consumer
New
CanadaFull-TimeStaff
Salary not disclosed
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Job Details
- Experience
- 10+ years of industry experience in applied science or data science roles for Master’s degree holders, or 6+ years for PhD holders
- Required Skills
- PythonSQLETLData visualizationStakeholder managementData modelingR
Requirements
- Master’s degree or PhD in Statistics, Mathematics, Economics, Physics, Operations Research, or a related quantitative field
- 10+ years of industry experience in applied science or data science roles for Master’s degree holders, or 6+ years for PhD holders
- Expert-level proficiency in SQL and relational databases
- Strong programming skills in Python and/or R for statistical analysis and modeling
- Proven experience using data to influence product strategy and business outcomes
- Strong understanding of experimentation frameworks, statistical analysis, and causal inference methodologies
- Ability to solve ambiguous problems using structured, hypothesis-driven, and data-supported approaches
- Excellent communication and stakeholder management skills, with experience presenting to senior leadership
- Demonstrated mentorship experience and ability to guide and elevate other data scientists
- Strong business acumen combined with curiosity, initiative, and a bias toward action
- Ability to communicate complex technical concepts clearly to technical and non-technical audiences alike
Responsibilities
- Identify strategic opportunities to improve user acquisition, engagement, retention, and overall product performance
- Conduct exploratory analyses and deliver actionable insights into user behaviors, community interactions, and product usage trends
- Influence product and business roadmaps through data-driven recommendations and strategic analysis
- Design, develop, and maintain business and product health metrics, including supporting ETL processes when needed
- Lead experimentation initiatives from hypothesis development and experimental design through analysis and recommendation delivery
- Apply statistical methods, causal inference techniques, and data modeling approaches to solve complex business problems
- Build self-service analytics tools and frameworks to improve data accessibility and literacy across teams
- Partner closely with product, engineering, and design stakeholders to ensure insights are integrated into product development decisions
- Mentor junior data scientists, promote analytical best practices, and contribute to scaling the impact of the data science organization
- Communicate complex technical findings effectively to both technical and non-technical audiences, including senior leadership
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