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Preply is a unicorn edtech platform (Series D, $150M) that connects 100,000+ tutors teaching 90+ languages to learners across 180 countries. The company is building human-led, AI-enhanced learning experiences at global scale.
You will join Preply's Data Chapter as a Senior Data Analyst embedded in the B2B domain. This is a high-impact individual contributor role reporting to B2B leadership, working closely with directors, finance, product, and cross-functional partners to drive strategic decisions through analytics.
Key Responsibilities:
- Partner with senior stakeholders to proactively identify analytical opportunities that unlock improvements in retention, revenue, and operational efficiency.
- Build and own the analytical framework leadership uses to evaluate B2B trade-offs and define long-term measurement frameworks that identify structural growth levers.
- Lead high-complexity, end-to-end analytical initiatives including retention and cohort analyses; uncover root causes behind revenue retention, LTV, churn, utilization, and cost efficiency; translate findings into concrete pricing, product, and lifecycle recommendations.
- Own impact modeling, scenario analysis, and KPI governance for B2B; resolve conflicting metric definitions across Operations, Finance, Marketing, and Product; maintain a single source of truth for quarterly and annual planning.
- Design the experimentation and analytics agenda; translate results into executive-ready storytelling that aligns stakeholders on goals and trade-offs.
- Partner with Directors and VPs to shape B2B strategy, embed analytics into daily decision-making, and mentor senior analysts.
You will work with a collaborative, high-performing team in a fast-paced environment where analytical rigor directly influences company strategy and resource allocation.
Requirements:
- 5+ years of experience in analytics roles, ideally in B2B, with demonstrated ownership of KPI frameworks and measurable impact on retention, revenue, or efficiency.
- Ability to point to specific decisions (pricing changes, resourcing calls, roadmap cuts) that resulted from your analysis, and judgment to explain cases where recommendations were rejected and why that was ultimately correct.
- Experience owning a metric or strategic framework that other teams were required to use; proven ability to resolve conflicts between teams with competing metric definitions.
- Deep understanding of retention and performance metrics (revenue retention, LTV, churn, utilization, cost efficiency); ability to build an LTV or cohort model from scratch.
- Strong, independent SQL skills; recognized as a peer reviewer for other analysts' code; proven ability to lead cross-functional analytical projects end-to-end.
- Strong business acumen and stakeholder influence; comfortable declining requests that aren't the right question, clarifying trade-offs, and building forecast/scenario models that leadership uses to defend strategic bets.
Nice to Have:
- Background in B2B SaaS, enterprise, or account-based business models; exposure to customer support operations.
- Experience building or scaling an analytics function (hiring, tooling, process, KPI frameworks).
- Hands-on experience with Looker, Snowflake, Tableau, or Power BI.
- Working knowledge of Python for analysis.
- Master's or PhD in a quantitative field.
