
Artificial Intelligence • SaaS • Enterprise
PlantingSpace is developing an advanced AI system that aims to represent knowledge and uncertainty to facilitate the discovery of insights and enable transparent problem-solving. The company is addressing the challenges of accessing and combining vast amounts of information spread across various mediums such as websites, databases, and scientific literature. Their system uses a probabilistic framework for reasoning and learning, making use of components like category theory, Bayesian statistics, and deep learning to improve the transparency and reliability of AI's reasoning capabilities. PlantingSpace's approach involves developing a universal language for representing heterogeneous information and employing a visual and natural language representation to make reasoning processes understandable. The company provides their AI services in various domains, acting as research assistants, analysts, or data scientists, and focuses on harnessing cutting-edge AI techniques to enhance analysis and problem-solving.
October 23

Artificial Intelligence • SaaS • Enterprise
PlantingSpace is developing an advanced AI system that aims to represent knowledge and uncertainty to facilitate the discovery of insights and enable transparent problem-solving. The company is addressing the challenges of accessing and combining vast amounts of information spread across various mediums such as websites, databases, and scientific literature. Their system uses a probabilistic framework for reasoning and learning, making use of components like category theory, Bayesian statistics, and deep learning to improve the transparency and reliability of AI's reasoning capabilities. PlantingSpace's approach involves developing a universal language for representing heterogeneous information and employing a visual and natural language representation to make reasoning processes understandable. The company provides their AI services in various domains, acting as research assistants, analysts, or data scientists, and focuses on harnessing cutting-edge AI techniques to enhance analysis and problem-solving.
• Discovery and synthesis of the vision and value proposition of our product • Translate user and market research into clear product opportunity briefs linking technology capabilities with user needs • Own a prioritized pipeline of use cases, with validation status (validated, invalidated, in testing) • Build a deep understanding of the technology: its longer-term potential, current limitations, and its position in the competitive landscape • Define and execute validation frameworks for new use cases, with measurable outcomes • Communication of the product vision to various stakeholders • Produce and maintain a living product narrative (decks, docs, demos) tailored to each audience • Ensure consistent messaging across website, recruitment, investor updates, and user interactions • Run regular internal briefings to keep the team aligned on product vision • Definition of a detailed vision for the user’s journey and interaction with our system • Deliver and maintain a user journey map with touchpoints, workflows, and pain points • Create prototype flows (wireframes or mockups) to test assumptions with users • Owning the implementation of a defined user journey and experience • Collaborate with engineering on scoping goals/tasks per milestone sprint • Communicate structured user insights reports to the team after each pilot phase • Drive continuous iteration by coordinating design + engineering to address gaps surfaced in pilots
• Experience and track record along the areas of responsibility as highlighted above • Fast learner – able to quickly understand sophisticated functionality and user workflows, and translate them into product directions • Proven track record in high-intensity, fast-moving environments (e.g. startups, consulting, finance, research) where they delivered under uncertainty • Strong communicator – equally credible with engineers, researchers, users, and investors; proven ability to communicate complex technologies to different audiences • Hands-on builder – not just a coordinator: willing to prototype, test, write • User empathy – able to engage with demanding professional users and turn feedback into clear product priorities • Deep-tech exposure – experience working on products built from new or complex technology • Industry alignment – ideally experience in investment research, asset management, or quantitative finance (e.g. building valuation models or analyzing distressed situations) • Education – advanced degree in a technical/quantitative discipline (e.g. CS, physics, finance, economics) or equivalent experience.
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Apply NowOctober 23
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