Data Scientist - Inference, Safety and Customer Care
$108,000–$135,000 year
HybridToronto, Ontario, Canada
Job Summary
Design rigorous experiments and quasi-experiments to measure the causal impact of SCC product and AI-agent launches, driving data-informed decisions for high-stakes support interactions. Build causal ML models to optimize concession budget allocation and quantify long-term effects on rider and driver retention. Develop frameworks analyzing tradeoffs between accuracy, coverage, user experience, and operational cost to empower leadership on scaling AI-powered support. Collaborate cross-functionally with Product, Engineering, and Operations to deliver strategic insights that balance service quality and business impact. Communicate learnings to stakeholders to drive informed, data-driven decision-making across the team.
Required Qualifications
- 2+ years of industry experience in causal inference or data science
- Master's degree in a quantitative field (statistics, economics, computer science, etc.), or a PhD in a relevant field
- Strong knowledge of causal inference and experimental design
- Experience with uplift modeling / heterogeneous treatment effect (CATE) estimation
- Proven ability to apply statistics to unstructured problems and deliver measurable results
- Expertise in SQL
- Experience with large-scale data platforms
- Proficiency in Python
- Proven ability to communicate clearly and effectively to audiences of varying technical levels
- Excellent project management, communication, and collaboration skills
- Experience partnering with operational teams and support systems (customer care workflows, agent operations, or credit budget allocation)
- Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays
Desired Qualifications
- Experience working with AI/LLM applications (LLM-powered agents, retrieval systems, or evaluation frameworks)
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