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Jobs/Senior Data Scientist Role/preply - Senior Data Strategy & Operations Lead
preply

preply - Senior Data Strategy & Operations Lead

London, Greater London, United Kingdom2w ago
In OfficeStaffEMEAArtificial IntelligenceEdTechSenior Data ScientistTeam LeadDocumentationClaudeCursorTeam LeadershipGoal Setting

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Requirements

• 7+ years of experience in strategy, operations, or planning, ideally in a high-growth tech environment. • Hands-on experience working closely with data, analytics, or AI/ML teams: you understand how these teams operate, what they deliver, and what slows them down. • Technical familiarity: you can follow conversations about data pipelines, ML models, experimentation frameworks, and AI product features without needing everything translated. You are not expected to write code, but you should be comfortable in technical environments. • Proven track record running operating cadences (OKRs, roadmap reviews, business reviews) and driving cross-functional alignment in complex organisations. • Strong program and project leadership: you take ambiguous, cross-functional problems from definition to delivery with minimal hand-holding. • Excellent stakeholder management: you build trust with both technical and non-technical leaders, communicate with clarity, and know how to influence without authority, including executive leadership. • Highly data-driven: comfortable building models, spreadsheets, and dashboards to inform decisions. SQL or BI tool experience (e.g., Looker, Tableau) is a plus. • Exceptional bias to action: you keep momentum high, unblock work proactively, and know how to get things done in fast-moving environments. • Strong written and verbal communication skills, with experience producing executive-level updates, presentations, and documentation. • Proficient user of AI tools (e.g., ChatGPT, Claude, Copilot, Cursor): you actively use AI to accelerate your work, whether for drafting, analysis, research, or automation, and you stay current with how these tools are evolving. • Previous experience as a data analyst, data scientist, or in a technical role before moving into strategy/operations. • Familiarity with AI/ML product development lifecycles and the specific challenges of shipping AI-powered features. • Experience with marketplace or edtech businesses. • SQL fluency and comfort working directly with data tools. • Experience supporting VP or C-level leaders as a strategic partner or Chief of Staff-type role. • Care to change the world - We are passionate about our work and care deeply about its impact to be life changing. • We do it for learners - For both Preply and tutors, learners are why we do what we do. Every day we focus on empowering tutors to deliver an exceptional learning experience. • Keep perfecting - To create an outstanding customer experience, we focus on simplicity, smoothness, and enjoyment, continually perfecting it as every detail matters. • Now is the time - In a fast-paced world, it matters how quickly we act. Now is the time to make great things happen. • Disciplined execution - What makes us disciplined is the excellence in our execution. We set clear goals, focus on what matters, and utilize our resources efficiently. • Dive deep - We leverage business acumen and curiosity to investigate disparities between numbers and stories, unlocking meaningful insights to guide our decisions. • Growth mindset - We proactively seek growth opportunities and believe today's best performance becomes tomorrow's starting point. We humbly embrace feedback and learn from setbacks. • Raise the bar - We raise our performance standards continuously, alongside each new hire and promotion. We build diverse and high-performing teams that can make a real difference. • Challenge, disagree and commit - We value open and candid communication, even when we don’t fully agree. We speak our minds, challenge when necessary, and fully commit to decisions once made. • One Preply - We prioritize collaboration, inclusion, and the success of our team over personal ambitions. Together, we support and celebrate each other's progress. • DIVERSITY, EQUITY, AND INCLUSION

Responsibilities

• OPERATING CADENCE & PLANNING • Own and run the operational rhythm of the Data & Applied AI org: team syncs, roadmap reviews, OKR cycles, quarterly planning, and retrospectives. • Lead the annual and quarterly planning processes for the team, linking data and AI initiatives to company-level goals and product strategy. • Manage the VP's leadership calendar and key team meetings, including agenda setting, preparation of materials, coordination with presenters, and follow-ups for cross-functional reviews, executive updates, and offsites. • Own the preparation cycle for leadership forums and company-wide reviews where the Data & Applied AI team presents: ensuring the right content, framing, and data are ready. • CROSS-FUNCTIONAL ALIGNMENT & STAKEHOLDER COMMUNICATION • Serve as the connective tissue between the Data & Applied AI team and Product, Engineering, Commercial, and other functions, ensuring priorities are aligned and dependencies are visible. • Own stakeholder communication: regular updates, progress reports, and dashboards that give leadership and partner teams clarity on what the team is delivering and why. • Represent the Data & Applied AI team in company-wide planning processes (e.g., product planning, OKR alignment, resource allocation). • PROJECT TRACKING & DELIVERY • Track progress on key data and AI initiatives end-to-end, from scoping through delivery, identifying risks early and driving resolution. • Support the VP in managing the team's portfolio of work: ensuring the right things are prioritised, resourced, and moving forward. • Drive accountability across workstreams without being a bottleneck, using lightweight but effective tracking and reporting mechanisms. • OPERATIONAL IMPROVEMENT & EFFICIENCY • Continuously identify friction in how the team works, whether in processes, tooling, collaboration patterns, or information flow, and design practical improvements. • Build and maintain scalable processes that help the team operate efficiently as it grows (e.g., intake workflows, documentation standards, knowledge sharing). • Support headcount planning, resource allocation, and team capacity analysis with data-driven models. • STRATEGIC INITIATIVES • Lead or support high-impact strategic projects that span the Data & Applied AI org, such as evolving the team's operating model, defining AI adoption frameworks, or assessing build-vs-buy decisions for data infrastructure. • Conduct analysis and research to inform key decisions: sizing opportunities, benchmarking approaches, or evaluating trade-offs.

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