# Domain Expert Partnerships at PlantingSpace > Remote · region unclear · Unspecified · Other · open. Source: https://alderhq.app/jobs/ashby%3APlantingSpace%3A7ac80521-a962-40f1-abef-4ad24f4e789c (read 2026-11-10). ## Facts (observed) - Company: [PlantingSpace](https://alderhq.app/companies/plantingspace) - Location text: Remote - Where it can be done from (inferred): Remote · region unclear (evidence: "Remote, region not stated") - Posted: 2026-02-18 (265 days ago) - First seen by alder: 2026-11-07 · last verified: 2026-11-08 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://jobs.ashbyhq.com/PlantingSpace/7ac80521-a962-40f1-abef-4ad24f4e789c ## Pay and sponsorship - Posted pay: not posted ## Description (the employer's text) We're building a system that represents domain knowledge as modular probabilistic models — making analysis rigorous and transparent by design. Users can connect these models flexibly into larger structures. The system enforces consistency across them, and propagates uncertainty through every step. Our first applications are in finance and scientific research, with use cases ranging from equity valuation and distress monitoring, to particle physics. We are seeking domain experts to collaborate with us on developing high-value use cases that leverage our system’s unique capabilities. Rather than acting as traditional consultants; we need builders and practitioners who are ready to integrate these solutions directly into pilot users’ workflows, drawing on their established industry networks to drive real-world adoption. ### Your profile Deep domain expertise — You are a current or former practitioner with hands-on experience solving complex problems in your field Technical understanding — You possess a strong grasp of statistical modeling, enabling close collaboration with our engineers on developing solutions Industry connections — You bring a network of relevant contacts, to identify and engage as pilot users ### Your field of expertise We are actively seeking to develop: Valuation Modes Quantitative Default-Probability Models Interest Rate Prediction Models …and more within the Financial Analysis space ### What Makes a Viable Use Case ### Problem Characteristics No existing AI solution — Problems currently handled mostly manually or through custom programming by engineering teams Clear pain points in current solutions — E.g., existing approaches (Excel models, custom programs) are brittle, hard to validate, don't integrate varied data sources easily, and require manual updates as they don't 'learn' from new information. Difficulty identifying inconsistencies within the model, or between the model and related knowledge autonomously. Statistical nature with uncertainty — Problems characterised by significant uncertainty, yet involving discoverable rules and causal chains that can be modeled ### Use Case Requirements Validated pain points — Pain points are serious enough that practitioners are willing to collaborate and ultimately engage in commercial pilot contracts Strategic fit with our system’s capabilities and long term product vision Identified pilot users — You have established contacts with industry practitioners actively using the relevant workflows, who are interested in validating solutions and quality checking the model ### Engagement Process Our collaboration follows a structured 4-stage development cycle: Stage 1: Opportunity identification - We establish together whether this is a relevant use case for us, and sketch the initial solution architecture. Stage 2: Validation - The goal of this stage is to establish the problem solution fit, commercial viability, and the ICP (ideal customer profile): with your help we will identify and jointly interview numerous practitioners, and ideally secure pilot user engagements. Stage 3: Specification & Implementation - You collaborate with our engineers to translate the validated solution architecture into a working model within our system, and participate actively in user testing with our pilot users. Stage 4: Production - Transitioning from pilot to sustained, production-grade usage. You support the integration into users' existing tools and help identify opportunities for expansion. ### Collaboration & Compensation Our compensation model is designed to support you through the early exploration phases while offering significant upside for successful outcomes. Our compensation has two components: Competitive per-diem rates and engagement via self-employment/contractor, billed via time tracking to PlantingSpace AG (a Swiss company). Participation in Commercial Success: Opportunity to participate in gross profit sharing from jointly established user engagements. ### Next Steps If you have expertise in a relevant domain and connections to potential pilot users, we would love to hear from you. To discuss a potential collaboration, please complete the application form, including: --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/ashby%3APlantingSpace%3A7ac80521-a962-40f1-abef-4ad24f4e789c and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.