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 organizing large-scale data for scoring and analysis.
  • Design and operate web scrapers to extract signals from nonprofit websites, including products used, payment tools, and vertical indicators.
  • Develop ML filters and classifiers, including a binary model to identify fundraising websites and other prospect-quality signals.
  • Source and integrate financial and third-party data from nonprofit registries, SimilarWeb, and Facebook.
  • Structure enriched datasets in internal databases so they can be used across the team for research and analysis.
  • Partner with the sales team to define qualification criteria and analyze disqualified Salesforce accounts to refine scoring logic.
  • Deploy the scoring model and integrate its outputs into Salesforce in a maintainable way.
  • Build a scraper to monitor existing clients’ websites and verify proper Fundraise Up implementation across properties.
  • Develop robust, cost-efficient filtering pipelines to handle noisy, duplicate data at large scale.
  • Break the project into targeted sub-models for different verticals and geographies as needed.

Requirements

  • 5+ years of ML/DS experience solving real product problems.
  • Strong expertise in ML and mathematical statistics, including classical algorithms such as gradient boosting and modern NLP/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 metrics such as conversion rate and LTV.
  • Strong Python skills with a product-oriented approach, clean code practices, and knowledge of design patterns.
  • Advanced SQL and the ability to build complex datasets in ClickHouse, plus experience 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 the right tech stack, and deliver to production independently.
  • Strong English communication skills at C1 level.
  • Experience with uplift modeling, causal ML, or OpenAI-based RAG and prompt engineering is a plus.
  • Experience with Airflow, MLflow, FastAPI, Pydantic, Redis, pandas, or Polars is a plus.

Benefits

  • 31 days off.
  • 100% paid telemedicine plan.
  • Home office setup assistance, including furniture and equipment such as a chair, desk, and monitor.
  • English learning courses.
  • Relevant professional education support.
  • Gym or swimming pool access.
  • Co-working support.
  • Remote working.
  • Equity options.

Interested in this position?

Apply directly on the company website

Apply Now

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