{"version":"0.1","company":{"name":"YubHub","url":"https://yubhub.co","jobsUrl":"https://yubhub.co/jobs/skill/plg-motions"},"x-facet":{"type":"skill","slug":"plg-motions","display":"Plg Motions","count":1},"x-feed-size-limit":100,"x-feed-sort":"enriched_at desc","x-feed-notice":"This feed contains at most 100 jobs (the most recently enriched). For the full corpus, use the paginated /stats/by-facet endpoint or /search.","x-generator":"yubhub-xml-generator","x-rights":"Free to redistribute with attribution: \"Data by YubHub (https://yubhub.co)\"","x-schema":"Each entry in `jobs` follows https://schema.org/JobPosting. YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_87cfb794-843"},"title":"Data Scientist","description":"<p>Replit is redefining how software is built and who gets to build it. Our mission is Autonomy for All , making programming accessible, collaborative, and powered by AI.</p>\n<p>This role owns how Replit understands its customers across every touchpoint. You&#39;ll build the analytics and intelligence layer that spans marketing performance, customer signals, and support , turning massive volumes of behavioural data, feedback, and interaction signals into insights that drive growth, retention, and revenue.</p>\n<p>You will:</p>\n<ul>\n<li>Design and analyse marketing experiments across paid, lifecycle, and content channels; optimise CAC, LTV, and ROAS</li>\n<li>Build multi-touch attribution and marketing mix models to understand what&#39;s driving growth</li>\n<li>Synthesise customer signals , support tickets, social, reviews, CSAT , into automated intelligence that reaches the teams who need it</li>\n<li>Build churn and retention models to identify at-risk users and inform lifecycle intervention strategies</li>\n<li>Define and maintain customer segmentations and personas that drive targeting, messaging, and product decisions</li>\n<li>Build the analytical foundation for Voice of the Customer , connecting qualitative feedback signals to quantitative behaviour data at scale</li>\n<li>Detect emerging product issues and bugs faster by surfacing support signal early enough to shape engineering priorities</li>\n<li>Optimise automation and deflection to reduce support load and improve self-serve resolution rates</li>\n<li>Build the measurement foundation to fully optimise ROI across all support activities</li>\n<li>Use LLMs and agentic workflows to analyse unstructured data at scale and automate recurring analysis</li>\n<li>Create automated reporting that puts key metrics to inform the company</li>\n</ul>\n<p>Required Skills and Experience:</p>\n<ul>\n<li>6+ years of experience in data science with a focus on marketing, growth, or customer analytics</li>\n<li>Strong SQL skills and experience with large-scale event-level user behaviour data; 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