GoFundMe is looking for a Staff Data Scientist to drive the evolution of Sales Intelligence, aiming to enhance how their Sales and Customer Success teams acquire, retain, and grow non-profit (NPO) partners by leveraging advanced machine learning and natural language models.
Requirements
- Advanced proficiency in Python (NumPy, pandas, scikit-learn) and SQL (window functions, performance tuning).
- Hands-on experience designing, analyzing, and interpreting A/B tests and experimentation frameworks.
- Expertise in statistical inference, causal modeling (regression, propensity scoring), uplift modeling, and marketing attribution models (multi-touch attribution, Markov chains).
- Proven track record in time-series forecasting and budget allocation models.
- Familiarity with ETL frameworks, data warehousing, and APIs; hands-on experience with Databricks and Snowflake is a plus.
- Data visualization skills using Looker or equivalent BI tools; strong storytelling and presentation abilities.
- Familiarity with vector databases (e.g., Pinecone, Weaviate, FAISS), embedding-based retrieval systems, and knowledge graph architectures
Responsibilities
- Lead the development of sales intelligence models: Design, prototype, and deploy models that score leads, predict churn, and surface upsell and cross-sell opportunities across our NPO customer base.
- Develop and evolve customer health frameworks: Build predictive models that quantify customer engagement, satisfaction, and retention risk, helping Sales and Success teams proactively address churn.
- Operationalize AI for sales enablement: Leverage NLP, embeddings, and large language models (LLMs) to extract, normalize, and retrieve insights from structured and unstructured sources - including sales notes, emails, call transcripts, CRM data, and support tickets - creating a unified knowledge layer for intelligent sales workflows.
- Build data-driven playbooks: Create systems that recommend relevant talking points, products, or case studies for sales meetings based on historical interactions and customer attributes.
- Advance predictive and prescriptive modeling: Develop time-series and optimization models to forecast sales outcomes and recommend next-best actions for account growth.
- Partner with GTM systems and data engineering: Ensure robust data pipelines, feature stores, and feedback loops that enable continuous model improvement.
- Act as a technical thought leader: Define best practices for model validation, feature engineering, and productionization in go-to-market (GTM) AI applications.
Other
- Candidates considered for this role will be located in the San Francisco, Bay Area.
- There will be an in-office requirement of 3x a week.
- 8+ years of experience in data science or applied ML, with at least 4–5 years focused on sales analytics, revenue intelligence, or customer lifecycle modeling.
- Master’s or Ph.D. in a quantitative discipline (Statistics, Economics, Computer Science, Mathematics, or related field) or equivalent applied experience.
- Exceptional communication skills: able to influence non-technical stakeholders and present complex analyses to executive audiences.
