Nansen

• You own the full sales cycle in the staking vertical. Foundations, ecosystem teams, institutional holders — these are your prospects. From first outreach to signed contract, from renewal to expansion, this is your book. • Own the complete sales cycle: prospect, qualify, close, renew, and expand partnerships with blockchain foundations and ecosystem teams • Manage the end-to-end launch of new validator ecosystems: initial scoping, commercial negotiation, delegation activation, and go-to-market execution • Identify and engage institutional holders and ecosystem leads who need staking infrastructure and validator partnerships • Track new chain launches, protocol developments, and market shifts to find opportunities before they're obvious • Partner with product, marketing, and customer success to close complex deals and retain accounts

• You own trading revenue. Not "influence" it. Not "partner on" it. Own it. • Build and execute acquisition strategies for crypto-native traders. • Drive trading volume and fee revenue. • Find and fix activation blockers with product and engineering. If users sign up and don't trade, that's your problem to solve • Design incentive and referral mechanics that convert • Run the trading-focused affiliate program end-to-end: find the right creators, activate them, cut the ones who don't perform • Scale content and creator partnerships that drive real top-of-funnel • Run structured growth experiments: A/B tests, cohort analysis, channel tests. Shut down what isn't working before it becomes a habit • Lead a team of Growth Leads driving trading revenues. You set the bar, you hold people to it • Set direction and frameworks — then get out of the way and let the team execute • Hire as we scale. You'll build this function, not just manage it

• Conduct security reviews of systems, architectures, and code — proactively identifying and addressing vulnerabilities. • Serve as a go-to security advisor for engineering teams, helping them make secure design decisions. • Define and implement security standards across cloud infrastructure, applications, and blockchain systems. • Implement and maintain security tooling: vulnerability scanning, endpoint protection, SIEM, logging and monitoring. • Secure CI/CD pipelines and deployment workflows from a security perspective. • Secure internal AI tools and LLM integrations — from API key management and prompt injection prevention to evaluating the security implications of AI adoption across the organization. • Manage and improve secrets management, key management, and access control practices across the organization. • Define and maintain secure coding guidelines and security review processes for engineering teams. • Collaborate with external providers on penetration tests and security audits, ensuring findings are prioritized and remediated. • Participate in incident response: investigation, containment, root cause analysis, and post-incident improvements. • Support compliance and audit readiness by implementing required security controls and maintaining documentation.

• You'll build the intelligence layer that powers that mission. That means working with 500M+ labeled blockchain addresses, training models on data no one else has, and shipping AI/ML systems that help real investors make better decisions and grow their portfolios. • Design and build AI/ML models on top of the richest onchain dataset in the world — then make them fast, scalable, and production-ready • Work shoulder-to-shoulder with engineers and product to ship models that actually reach users • Stay ahead of the curve in both AI/ML and blockchain — this space moves fast, and we need someone who moves faster • Level up the team: mentor junior engineers, raise the bar on what good looks like • Own your work end-to-end; from data pipeline to deployed feature

• Build upon and scale our in-house product analytics solution, enabling self-serve analytics for teams across Product, Engineering, Design, Marketing and Sales • Leverage AI tools (Claude Code, Cursor) as core productivity multipliers in your daily workflow - we expect 10x productivity gains through AI-first approaches • Interpret complex data sets and communicate insights effectively to both technical and non-technical audiences • Translate business requirements into technical requirements for engineers • Manage and evolve our in-house customer data platform, ensuring accurate tracking implementation and maintaining data taxonomy • Analyse user behaviour and product metrics for our analytics, trading and staking products, translating insights into actionable product improvements • Enhance quantitative analyses with qualitative insights derived from user studies and feedback • Build and maintain data models and transformations using dbt

• Develop and own core data models that enable faster, better decisions across the organisation • Design, develop, and support data pipelines, warehouses, and reporting systems to solve business operations, user, and product problems • Build internal tools leveraging AI to 10x team productivity and enable self-serve analytics • Work closely with analysts and finance to create, test, and maintain data models for our analytics, trading, and staking products • Transform and model blockchain data (on-chain transactions, DeFi protocols, trading activity) into actionable datasets • Take initiative and ownership of solutions to data quality and workflow challenges • Drive scalable approaches to data governance and observability • Leverage AI tools (Claude Code, Cursor) throughout the development lifecycle - from SQL generation to pipeline development to documentation