Fundraise Up

Fundraise Up

Fundraise Up specializes in enhancing online donation processes through AI-driven conversion optimization and integrated payment solutions, enabling organizations to maximize their fundraising potential and improve donor engagement.

Capital Markets
51-250
Founded 2017

Description

  • Build a market intelligence database by collecting, enriching, and structuring data from multiple sources.
  • Design and operate web scrapers to extract signals from nonprofit websites, including products used, payment tools, and industry indicators.
  • Develop machine learning filters and scoring models to identify fundraising-related websites and high-potential prospects.
  • Source and integrate financial and third-party data from nonprofit registries, SimilarWeb, Facebook, and similar sources.
  • Store enriched datasets in the internal database and make them usable for research and analysis across the team.
  • Work with the sales team to understand qualification criteria and analyze disqualified accounts in Salesforce to refine scoring logic.
  • Deploy the scoring model and integrate outputs into Salesforce in a maintainable way.
  • Build a scraper to monitor existing client websites and verify correct implementation of Fundraise Up tools.
  • Create robust, cost-efficient data pipelines that handle duplicates, inconsistent data, and large-scale noise.
  • Develop targeted sub-models for specific verticals and geographies as the initiative evolves.

Requirements

  • 5+ years of ML/DS experience solving real product problems.
  • Strong expertise in machine learning and mathematical statistics, including classical algorithms such as gradient boosting.
  • Understanding of modern NLP and LLM approaches.
  • Proven experience with large-scale web scraping and data pipeline construction.
  • Metrics-driven mindset with the ability to connect ML metrics such as ROC-AUC, F1, and RMSE to business outcomes.
  • Strong Python skills with a product-oriented approach, clean code practices, and knowledge of design patterns.
  • Advanced SQL skills, including building complex datasets in ClickHouse and working with MongoDB.
  • Hands-on MLOps experience with experiment tracking and production workflows such as Docker, Git, and CI/CD.
  • Ability to break down ambiguous problems, choose an appropriate tech stack, and deliver to production independently.
  • Experience with distributed systems or Linux server administration is a plus.
  • Familiarity with CatBoost, uplift modeling, OpenAI, MLflow, Airflow, Grafana, Sentry, pandas, Polars, Redis, FastAPI, and Pydantic is a plus.
  • Strong English proficiency at C1 level.
  • Ability to communicate complex analytical concepts to non-technical audiences is a plus.

Benefits

  • Private medical insurance for the employee and their family.
  • 23 paid vacation days per year.
  • 11 paid public holidays per year.
  • 5 company-paid sick leave days.
  • English learning courses.
  • Relevant professional education support.
  • Gym or swimming pool benefit.
  • Home office setup assistance for furniture and workspace equipment.
  • Co-working support.
  • Remote working.
  • Equity options.

Interested in this position?

Apply directly on the company website

Apply Now

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