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Director, Analytics & Decision Intelligence

Everway
CompanyEverway
CategoryUncategorised
LocationRemote- UK
RemoteRemote
EmploymentNot stated
LevelNot stated
SalaryNot stated by the employer
Posted27 May 2026
Last verified4 Aug 2026
SourceEmployer ATS (greenhouse)
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Description
Every mind is unique. Yet much of the world is still built for what’s considered "normal," leaving too many people behind. At Everway, we change that by creating technology that helps everyone understand and be understood. By understanding and addressing the unique needs of each individual, we're creating a world where differences are recognized and valued. Our careers fit real life. When you join us, you’re not just taking a job. You’re joining a movement to build a more neuroinclusive world. We’re a global community of over 800 employees spanning North America, UK, Europe, Australia, and New Zealand. A career here is purposeful and fast-moving, with clear expectations, modern tools, and the clarity to focus on what matters most.  Our people are supported and encouraged to show up as they are, with different ways of thinking welcomed and valued. We pride ourselves on our core values that are embedded within our culture. These are to be curious, have courage, and commit fully . Join us at Everway - together, we can unlock the full potential of every mind. About the role Every function at Everway — sales, finance, customer success, product — makes decisions every day that shape revenue, retention, and learner outcomes. Too many of those decisions are made without the data confidence they deserve. This role exists to change that. We're looking for someone to lead our analytics function with a decision-first mindset — someone who starts by understanding the decisions the business needs to make, then works backwards to design the data products, self-service experiences, and insight surfaces that make those decisions faster, more confident, and more consistent. You'll be building and leading a product-oriented analytics team that designs gold-tier data products with clear ownership, documented contracts, defined SLAs, and measurable impact on the decisions they serve. Outputs might be interactive dashboards, governed self-service datasets published from our Databricks lakehouse, embedded metrics, or AI-assisted exploration — but in every case, the measure of success is the same: did the decision get better? Reporting to the VP of Data, you'll work closely with stakeholders across the business to map critical decision points and uncover the ones the business hasn't identified yet — surfacing risks, patterns, and opportunities that would otherwise go unseen. You'll partner with data engineering on data contracts and gold layer design, and play a hands-on role in shaping how we adopt AI-powered analytics — from natural language interfaces to LLM-assisted workflows — always within a governed framework. Responsibilities Map and prioritise the organisation's critical decisions. Work across product, sales, finance, customer success, and leadership to identify the highest-impact decisions in each domain, understand how they're currently made, and define what data — at what quality, freshness, and granularity — would materially improve them. Proactively surface what the business hasn't seen. Go beyond answering known questions — use exploratory analysis, anomaly detection, and cross-domain pattern recognition to identify risks, opportunities, and emerging trends that stakeholders haven't asked about yet. The best analytics functions don't just support decisions — they trigger them. Lead the analytics function as a product team — setting the vision, owning the roadmap, and establishing the operating model. The backlog is organised around decisions to be supported, not requests to be fulfilled. Design and deliver gold-tier data products with clear ownership, versioning, documented data contracts, and defined SLAs — treating every analytics output as a product with a lifecycle, users, and success metrics tied to decision outcomes. Architect and own the self-service analytics model — defining tiered access (raw, curated, pre-built), designing governed explorat
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