Data Scientist for B2B SaaS Revenue Analytics

We are a growing B2B SaaS company looking for a data scientist to help us understand revenue, pipeline, customer behavior, and growth performance. Our data lives across HubSpot, Salesforce, Stripe, marketing platforms, spreadsheets, and internal databases. We need someone who can clean messy data, find patterns, and turn analysis into clear business decisions. The first project will focus on: Lead source performance Sales funnel and pipeline bottlenecks Customer segmentation Retention and churn signals LTV, CAC, and revenue forecasting Weekly KPIs for leadership You should be strong with SQL, Python, Pandas, data cleaning, statistical analysis, dashboards, and business reporting. Experience with SaaS, RevOps, GTM analytics, marketing analytics, CRM data, or subscription revenue data is a strong plus. We are not looking for someone who only builds charts. We need someone who can connect the data to the business problem and explain what should happen next. To apply, please share one real project where you used data science or analytics to solve a business problem. Include the industry, data sources, methods used, and business result.