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
The Demand Forecasting team is at a pivotal, high-growth stage. This role is highly dynamic, requiring a blend of technical depth and exceptional communication to adapt our platform to real-world customer data and challenges. You will be a critical link between the core product and our clients’ business success.
Responsibilities
- Lead and support customer-facing Demand Forecasting use cases from discovery through deployment
- Work hands-on with customer data to design, test, and validate forecasting solutions
- Act as a trusted analytical and technical advisor to customers, deeply understanding their business context and datasets
- Analyze and explain model outputs and complex analytical concepts in a clear, business-oriented way
- Troubleshoot technical and data-related challenges and drive them to resolution
- Collaborate closely with Data Science and Customer Success teams, providing structured feedback from customer use cases
- Help customers achieve measurable business impact and adoption of Pecan’s Demand Forecasting module
What We Are Looking For
- 2–5 years of real-world experience in technical, data, solutions, analytics, or implementation roles
- Proficient in Python, SQL, and Spark
- Solid experience working with structured data and Python
- Strong technical debugging and problem-solving mindset
- Customer-facing experience with the ability to lead technical conversations
- Excellent communication skills and ability to explain technical concepts clearly
- Highly organized and able to manage multiple implementations in parallel
- Experience in B2B / SaaS environments — a strong advantage
- Experience working with Customers (in English) – a must
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Use Cases
Customer Churn
Customer LTV
Campaign ROAS
Demand Forecast
Upsell and Cross-Sell
Lead Scoring
Customer Winback
Fraud & Chargeback Prevention
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