• Drive ownership - Own and evolve the existing structured financial data taxonomy library at AlphaSense, inclusive of all client-facing labels, metric definitions and dataset classifications, ensuring both backwards compatibility and future proofing. • Set the standard - Understand existing naming standards and define how label conventions and governance principles apply across a growing range of data types, ensuring clients can intuitively discover, understand, and leverage the data Alpha-Sense has to offer. • Collaborate cross-functionally with engineering, data, product, sales, and client-facing teams to align stakeholders on taxonomy decisions and translate conceptual frameworks into scalable, production-ready systems • Serve as the internal subject matter expert on data semantics, and develop and maintain official internal and external documentation ensuring taxonomy standards are clearly articulated and accessible to all stakeholders • Proactively identify gaps and inconsistencies as new datasets are onboarded, and drive resolution in a structured and scalable way • Design and maintain taxonomy and data structures with AI and LLM compatibility as a core consideration, ensuring labels, definitions, and conventions support model training, inference, and broader AI-driven automation • Lay the foundation for a future taxonomy practice — building repeatable frameworks and positioning this function for team growth over time

• Own the full product roadmap for the Agent pillar — unified Agent backend, Agent Drafts, AI Answers, Agentic Actions, Docs automation, and workflow amplification • Drive the consolidation of Drafts and AI Answers onto a single backend system, enabling the full Agent capability set to compound from a shared foundation • Define the experience and configuration UX that moves customers up the trust ladder — from "let me review that draft" to "handle it without me" • Shape how the Agent monetizes: resolutions, drafts, handoffs, and docs improvements are all outcome-priced surfaces; you'll own the logic for how customers experience and pay for each • Partner closely with the Intelligence and Conversations PMs — Agent needs signals from Intelligence and coordination with Conversations to work as a coherent system, not a feature stack • Spend real time with customers: understanding where they trust the AI, where they don't, and what would move them • Work with GTM and CS to ensure the Agent story is clear, the adoption motion is tight, and customer feedback loops back into the roadmap

• Own the full product roadmap for the Intelligence pillar: Topics, Sentiment detection, CX Score, and contact/company profiles enriched with conversation data • Ship the near-term: get Topics and Sentiment in front of customers fast, with a clear value signal — then use what you learn to sequence what comes next • Define the conversion moment: CX Score and churn risk alerts are the features that make a customer want to pay for Understand. You'll own how those land and what they trigger • Treat Intelligence as a shared primitive, not a standalone product. Signals from this pillar need to be accessible to the Agent and Conversations pillars — you'll coordinate those interfaces actively • Partner with the Gateway and Data teams to ensure the underlying infrastructure can support the aggregates Intelligence depends on, especially as CRM and lifecycle data start flowing in • Spend time with customers: support leads, ops managers, and the business owners who care about what support data can tell them • Work with GTM on the messaging for Understand — this is a net-new category for Help Scout and the story needs to land clearly

• Investigate design challenges with depth — explore multiple approaches, evaluate tradeoffs, and arrive at a clear, well-reasoned point of view • Articulate design decisions with conviction: why a path was chosen, what alternatives were considered, and what was intentionally left out • Demonstrate a high bar for what good looks like — backed by evidence from your portfolio and process • Translate technically complex product concepts into experiences that feel intuitive and effortless • Design for both admin and end-user personas — audiences with fundamentally different mental models, workflows, and risk tolerances • Reduce cognitive load without reducing capability; make hard things feel easy • Own and evolve a design system and component library that scales across Windows, Mac, web, and mobile • Apply deep knowledge of platform-specific design standards while maintaining a unified PreVeil identity • Ensure every surface feels like one product — not four separate apps • Drive the full design lifecycle: discovery, user research, wireframing, prototyping, high-fidelity design, and developer-ready handoff • Produce clear, complete specs that engineering can act on without ambiguity or back-and-forth • Actively use AI tools to accelerate iteration, sharpen craft, and explore ideas faster • Conduct and synthesize user research to build a genuine picture of how users think, work, and struggle • Bring evidence of user needs into every design decision — not just instinct • Identify behavioral patterns across users and translate them into better product decisions • Partner closely with Product and Engineering — communicate clearly, show work early, and iterate based on real feedback • Be the designer people can count on: have great quality designs that are well thought through, meet commitments, and surface issues proactively • Work with a low ego and a maker-first mindset — this is a hands-on, high-output role