
Job Overview
Location
United States
Job Type
Full-time
Category
Data Science
Date Posted
April 15, 2026
Full Job Description
📋 Description
- • As a Data Scientist at Reflow, you will design and build the algorithms that power the company’s workforce and workflow intelligence platform, turning complex data into clear, actionable value for customers by reducing manual configuration and enabling automation.
- • Day to day, you will develop models to pre-label, classify, and structure data; collaborate with ML engineers to productionize models; partner with product and engineering to translate business problems into data-driven solutions; analyze complex datasets to identify patterns and trends; and continuously evaluate and improve model performance for accuracy, reliability, and impact.
- • Reflow is a U.S.-based tech company building a globally distributed team with a high bar for talent, ownership, and execution, focused on creating a workforce and workflow intelligence platform that helps teams understand and improve how work gets done.
- • In this role, you will deepen your expertise in applied machine learning and product-driven data science, gain experience productionizing models at scale, and help define how intelligence is delivered through automation and insights that make users more effective in real-world workflows.
Skills & Technologies
About Reflow
Reflow is a cloud-based platform designed to automate and streamline the process of software updates for IoT devices. It provides a secure and reliable solution for managing firmware over-the-air (FOTA) deployments, enabling companies to efficiently deliver updates, patches, and new features to their connected products. The platform offers features such as staged rollouts, rollback capabilities, and detailed monitoring to ensure smooth and successful updates. Reflow aims to reduce the complexity and risk associated with device management, allowing manufacturers to maintain product security, enhance user experience, and extend the lifespan of their IoT ecosystems without manual intervention.
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