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Tier-1 brand and metro location increase competition, but specialized causal-inference growth focus reduces applicant pool.
Role demands SaaS growth analytics, experimentation, and privacy-first web tracking, making backgrounds less transferable.
Explicit 8+ years, senior technical leadership, and required causal inference and web-stack skills imply high selectivity.
Define and execute the global analytical strategy linking Slack’s web behavior metrics to business outcomes like customer acquisition and enterprise ARR.
Lead and innovate Slack’s web experimentation framework using advanced causal inference and statistical methods to measure true incremental lift.
Architect and scale the digital measurement ecosystem, predictive behavioral models, and automated reporting to support growth marketing insights and decision-making.
8+ years of experience in Data Science, Quantitative Analytics, or Growth Analytics, preferably in high-growth B2B SaaS or large-scale digital platforms.
Expertise in causal inference methods including CUPED, quasi-experiments, Bayesian and Frequentist statistics.
Proficiency in SQL and Python or R with experience in pathing analysis, propensity modeling, machine learning, and clustering.
Experience with web analytics tools (GA4, Adobe Analytics), server-side tracking, tag management, and operating in privacy-first, first-party data environments.
Senior individual contributor with the ability to bridge deep technical data science and strategic business decisions at executive levels.
Experienced leader or mentor capable of managing and elevating quantitative analytics teams and establishing analytical rigor across functions.
Strategic thinker focused on connecting digital experimentation metrics to big-picture business metrics such as enterprise pipeline velocity and customer LTV.