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Customer-Facing Data Scientist – Demand Forecasting - Pecan AI

  • חברה: Pecan AI
  • מיקום: רמת גן
  • רמת ניסיון: סניור
  • טכנולוגיות: Python, SQL, Spark

תיאור המשרה

Pecan is an automated, AI-based predictive analytics platform that simplifies and accelerates the process of building and deploying machine learning models across various business use cases. Learn more about our dedicated offering here: demandforecast.ai . Pecan connects to the raw data and completely automates the data preparation, engineering, and preprocessing phases, as well as the model training and evaluation lifecycle. It was acknowledged as one of Israel’s 50 most promising startups for two consecutive years. Company Highlights: Series C company with over

17M 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 a growing sales and marketing organization in the US Customers across CPG, retail, healthcare, mobile apps, fintech, insurance, and consumer services. Marquee customers include Johnson & Johnson, Mars, and SciPlay. Demand Forecasting Team The Demand Forecasting team is at a pivotal, high-growth stage. We have successfully built our core pipeline and are now aggressively onboarding new, diverse customers. This role is highly dynamic, requiring a blend of technical depth, proactive research, 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 As a key Customer-Facing Data Scientist on the Demand Forecasting team, you will: Work at the forefront of the data world, focusing on the optimization and deployment of Demand Forecasting models. Handle complex data science challenges using state-of-the-art techniques relevant to demand forecasting and time series, such as forecasting model ensembling, anomaly detection, feature engineering for trend/seasonality, and causal inference modeling. Act as a highly communicative partner to our clients, diving deep into their unique datasets to understand the nuances and challenges of their business. Lead the rigorous testing and application of our core ML pipeline on new customer data, identifying areas where it performs exceptionally well and researching/developing solutions for complex cases where it does not. Be instrumental in helping our clients achieve their business goals and realize the measurable value of Pecan’s Demand Forecasting module . Work within a production and product-oriented environment , ensuring models are robust, scalable, and directly integrated into the client’s operational workflow. What We Are Looking For 5+ years of experience as a data scientist working on tabular and time-series data BSc in a relevant field (e.g., Computer Science, Engineering, Statistics) Proficient in Python, SQL, and Spark Proven experience in creating measurable value with ML (defining KPIs, designing A/B tests, monitoring models in production) Deep experience with time series modeling and forecasting techniques Experience with AWS / Databricks – an advantage MSc/Research experience – an advantage Experience working with Customers (in English) – an advantage Apply for this job Resume * Pecan , Thank you for your application!

שאלות נפוצות על המשרה

איך מגישים מועמדות למשרת Customer-Facing Data Scientist – Demand Forecasting בPecan AI?

ההגשה למשרה זו מתבצעת באתר הגיוס של Pecan AI, דרך הקישור שבעמוד זה. ההגשה חינמית ואינה דורשת מנוי, ואפשר לשמור את המשרה ב-HiTakeJob כדי לעקוב אחריה.

איפה המשרה ממוקמת?

המשרה ממוקמת ברמת גן.

מה נדרש למשרת Customer-Facing Data Scientist – Demand Forecasting?

רמת ניסיון: סניור. טכנולוגיות מרכזיות: Python, SQL, Spark. הדרישות המלאות מופיעות בתיאור המשרה שלמעלה, כפי שפורסמו על ידי Pecan AI.

האם המשרה עדיין פעילה?

כן. המשרה פורסמה ב12 בספטמבר 2026 ומופיעה כפעילה במערכת הגיוס של Pecan AI. HiTakeJob בודק את המשרות מול המקור מדי יום, ומשרה שנסגרת מוסרת מהאתר.

אילו עוד משרות פתוחות בPecan AI?

כל המשרות הפתוחות של Pecan AI מרוכזות בעמוד החברה, יחד עם מידע על החברה וחוות דעת של עובדים.

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