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Strong Tier-1 brand, metro location, general Data Scientist title, and broad skillset raise competition.
Analytics methods are transferable, but web-experimentation and B2B SaaS domain knowledge increase sensitivity.
Explicit 8+ years plus deep causal inference, web-stack, and leadership requirements create strict filtering.
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Lead the analytical strategy and quantitative engine for Slack’s global web presence, connecting web behavioral insights to key business outcomes like customer acquisition and enterprise pipeline.
Own and evolve Slack’s global web experimentation framework, deploying advanced statistical methods to measure incremental lift and drive best practices across teams.
Architect predictive behavioral models and scalable data ecosystems while mentoring and potentially managing data analysts and scientists to elevate organizational analytics capability.
8+ years experience in Data Science, Quantitative Analytics, or Growth Analytics, preferably in high-growth B2B SaaS, enterprise tech, or large-scale digital platforms.
Expertise in causal inference, advanced statistical methods including CUPED, quasi-experiments, and Bayesian/Frequentist approaches.
Proficiency in SQL and Python or R; experienced with web analytics tools (GA4, Adobe Analytics), server-side tracking, and privacy-first data strategies.
Demonstrated leadership or mentorship experience with data science teams; executive communication skills to influence senior leadership.
Able to translate complex experimentation data into strategic growth narratives influencing VP/SVP and C-suite level decisions.
Operates at the intersection of technical data science and high-level business strategy with strong orientation to enterprise metrics like ARR, CAC, LTV.
Experienced in building and leading scalable analytics frameworks and teams within product and growth environments under privacy and data governance constraints.