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Senior Staff Data Scientist - Consumer Experimentation

RemoteCanada only
Published
Role
Data Science
Experience
Staff
Company size
Enterprise
Salary not disclosed
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Open to CA only. Set where you work from to check your eligibility.

No BS summary

Senior Staff Data Scientist for consumer experimentation, requiring deep causal inference and experimentation methodology expertise. Needs SQL plus R and/or Python, with 8+ years for Ph.D. holders or 12+ years for M.S. holders in applied science, data science, or experimentation-focused roles. Remote role located in Ontario, Canada.

Core skills

SQLR/Python

Optional skills

Bayesian experimental methodsBandit algorithmsAdaptive experimental designs

What you'll do

  • Serve as the technical authority on experimentation methodology across Consumer
  • Set standards for experiment design, analysis, and interpretation in a complex networked environment
  • Tackle spillover and network effects, interference between treatment and control, two-sided experimentation, and long-run effect estimation
  • Develop causal inference methods for cluster-randomized designs, switchback experiments, and synthetic control approaches
  • Design experimentation frameworks and guardrail metrics that account for ecosystem-level effects
  • Identify opportunities where improved experimentation methodology can unlock product insights
  • Build and scale self-serve experimentation tools, platforms, and best-practice documentation
  • Influence long-term product strategy through well-designed experiments and actionable recommendations
  • Mentor data scientists on experimentation best practices, causal reasoning, and statistical rigor
  • Publish and share methodological advances internally and externally where appropriate

What they require

  • Ph.D. in Statistics, Econometrics, Economics, Computer Science, or related quantitative field with strong focus on causal inference or experimentation methodology; or M.S. with equivalent depth of expertise
  • For M.S. holders: 12+ years of industry experience in applied science, data science, or experimentation-focused roles
  • For Ph.D. holders: 8+ years of industry experience in applied science, data science, or experimentation-focused roles
  • Deep expertise in causal inference, including network interference, spillovers, two-sided experimentation, switchback designs, cluster randomization, and/or synthetic control methods
  • Strong theoretical grounding in experimental design, including power analysis, variance reduction techniques, sequential testing, and multiple comparison corrections
  • Experience with experimentation platforms at scale
  • Track record of designing and analyzing experiments at scale in complex or networked environments
  • Ability to influence product and organizational strategy through experimentation insights
  • Ability to solve ambiguous, technically complex problems in a structured, hypothesis-driven way
  • Excellent communication skills for explaining nuanced statistical concepts to technical and non-technical senior stakeholders
  • Experience mentoring data scientists and building organizational capability in experimentation and causal reasoning
  • Comfortable in innovative and fast-paced environments with a bias toward action
  • Published research or industry contributions in interference in experiments, network experimentation, or marketplace causal inference preferred
  • Experience with social network or user-generated content platforms preferred

Benefits

  • Global benefit programs
  • Workspace support
  • Professional development support
  • Caregiving support
  • Family planning support
  • Gender-affirming care
  • Mental health and coaching benefits
  • Comprehensive medical benefits
  • Health Care Spending Account
  • Registered Retirement Savings Plan with matching contributions
  • Income replacement programs
  • Flexible vacation
  • Paid volunteer time off
  • Generous paid parental leave

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