About the role
Predictive Analytics Solution Engineer | Pecan AI Product How it works Product Tour Integrations Security Solutions Customer Churn Customer LTV Demand Forecasting Upsell & Cross-Sell Customer Winback Fraud & Chargeback Prevention Predictive Campaign ROAS Lead Scoring with Predictive Analytics Our Customers Case Studies Customers Videos Pricing Resources Blog Resource Center Podcasts Guides The Data Leader’s Guide to AI How to Build Your AI Strategy in 2026 AI for Subscription eCommerce 101 From Raw Data to AI Company
About Us Partners Careers Contact Us Newsroom DemandForecast.ai DemandForecast.ai Book a demo Pricing Book a demo Home → Careers → Predictive Analytics Solution Engineer Analytics Predictive Analytics Solution Engineer at Pecan Ai (View all jobs) Pecan is an automated AI-based predictive analytics platform. It simplifies and accelerates the process of building and deploying machine learning models in various business use-cases, such as life-time value, Churn, demand forecast and more. Pecan connects to the raw data and completely automates the data preparation, engineering and prepossessing phases, as well as the model training and evaluation lifecycle. It was acknowledged as one of Israel’s 50 most promising startups two years in a row Company Highlights: Series C company with over $117M raised to date . Tier-1 investors: Google Ventures (GV), Insight Partners, GGV, Dell Ventures, Mindset and S Capital. 50 employees HQ in Tel Aviv with growing sales organization in the US Customers across CPG, retail, healthcare, mobile apps, fintech, insurance, and consumer services. Marquee customers include Johnson & Johnson,, and SciPlay Typical Tasks: Guide and assist customers in utilizing the Pecan platform and implementing AI models. -Help customers understand complex AI concepts, identify relevant use cases, and implement solutions to drive business value. Address and resolve technical and data-related issues. Provide valuable feedback to the product team and collaborate to enhance the product. Analyze model outputs and explain complex ideas in a clear, understandable manner. Serve as the primary data and technical contact for clients, understanding and addressing their needs.
