Role: Senior ML-Engineer, Finance\nLocation: Spain, Remote\n\nWhat You’ll Do: Build a market intelligence data-base via collecting different types of data (scraping, enrichment), fixing data pipeline and creating an ML model for scoring and analysis of the raw data. Design and operate scrapers to extract key signals from nonprofit websites, including products used, payment tools, and industry vertical indicators. Develop critical filters such as an "Is this website for fundraising?" binary classifier, alongside other features that distinguish high-potential prospects. Source and integrate financial data from international nonprofit registries, as well as third-party signals from SimilarWeb and Facebook. Store and structure the enriched dataset in our internal database, making it accessible and useful across the broader team for research and analysis. Work closely with the sales team to understand their qualification criteria. Analyze disqualified accounts in Salesforce to identify common exclusion patterns and refine scoring accordingly. Deploy the scoring model and own the process of integrating outputs into Salesforce in a clean, maintainable way. Build a scraper to monitor existing clients' websites, tracking whether Fundraise Up tools are correctly implemented across their properties.