
201 - 500 employees
🛍️ eCommerce
🔌 API
🤝 B2B
eCommerce • API • B2B
Extend is a company that helps merchants generate revenue and protect their customers through modern product and shipping protection solutions. They offer protection plans from product failure and accidental damage to shipping issues like porch pirates and damaged deliveries. Extend provides a platform that is easy to integrate with eCommerce platforms like Shopify and BigCommerce. This enables merchants to easily offer protection plans and manage claims, with most being resolved in 90 seconds or less. The company focuses on improving profit margins and enhancing the customer experience by offering easy claim filing and turning customers into long-term advocates.
🕒 May 15
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201 - 500 employees
🛍️ eCommerce
🔌 API
🤝 B2B
eCommerce • API • B2B
Extend is a company that helps merchants generate revenue and protect their customers through modern product and shipping protection solutions. They offer protection plans from product failure and accidental damage to shipping issues like porch pirates and damaged deliveries. Extend provides a platform that is easy to integrate with eCommerce platforms like Shopify and BigCommerce. This enables merchants to easily offer protection plans and manage claims, with most being resolved in 90 seconds or less. The company focuses on improving profit margins and enhancing the customer experience by offering easy claim filing and turning customers into long-term advocates.
• Own the model lifecycle: requirements, experimentation, model development, evaluation, and model cards, partnering with ML engineers on deployment and production infrastructure • Translate complex fraud patterns into well-framed ML solutions: defining what to model, what success looks like, and where ML adds value vs. simpler approaches • Design and maintain feature engineering pipelines for model development • Monitor model quality in production, tracking performance over time, detecting data drift, and determining when to retrain • Partner closely with leadership, go-to-market, fraud operations, product, and engineering teams to define and execute effective fraud strategies • Champion a culture of continuous learning, experimentation, and collaboration across the fraud and broader data science teams
• Hands-on, proactive, and analytical professionals who are passionate about using data to solve complex, real-world problems • Bachelor’s degree or higher in a quantitative field such as Mathematics, Statistics, Computer Science, Engineering, Operations Research, Physics or related field • 3+ years of work experience building and deploying machine learning systems into production • Strong proficiency in Python and SQL • Strong understanding of ML fundamentals: model selection, evaluation methodology, feature engineering, and common failure modes • Hands-on experience with PyTorch, scikit-learn, and XGBoost (or similar gradient boosting frameworks) • High attention to detail, strong intellectual curiosity, and a deep understanding of user behavior and fraud patterns • Empathetic, humble, and collaborative team player • Candidates must be located within the continental United States
• Competitive salary based on experience, with full medical and dental & vision benefits. • Stock in an early-stage startup growing quickly. • Generous, flexible paid time off policy. • 401(k) with Financial Guidance from Morgan Stanley.
Apply Now🕒 May 15
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