
11 - 50 employees
Founded 2024
☁️ SaaS
🏢 Enterprise
🤝 B2B
SaaS • Enterprise • B2B
Reflow is a SaaS platform that provides enterprise teams real-time visibility into how operational work actually happens, helping them visualize workflows, identify bottlenecks and drift, prioritize data-driven automation, and measure ROI from optimization. Built as a system of record for enterprise operations, Reflow aggregates granular execution data across tools to surface objective insights, recommend high-impact automations (e. g. , refund processing, chargeback triage, subscription cancellations), and verify compliance with SOPs while maintaining enterprise-grade security and privacy controls.
🕒 April 15
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11 - 50 employees
Founded 2024
☁️ SaaS
🏢 Enterprise
🤝 B2B
SaaS • Enterprise • B2B
Reflow is a SaaS platform that provides enterprise teams real-time visibility into how operational work actually happens, helping them visualize workflows, identify bottlenecks and drift, prioritize data-driven automation, and measure ROI from optimization. Built as a system of record for enterprise operations, Reflow aggregates granular execution data across tools to surface objective insights, recommend high-impact automations (e. g. , refund processing, chargeback triage, subscription cancellations), and verify compliance with SOPs while maintaining enterprise-grade security and privacy controls.
• Design and build algorithms that power Reflow’s core intelligence and analytics capabilities. • Develop models to pre-label, classify, and structure data, reducing the need for manual setup by users. • Collaborate with machine learning engineers to productionize models and integrate them into scalable systems. • Partner with product and engineering to translate business problems into data-driven solutions. • Build and iterate on models that generate insights, predictions, and recommendations. • Help define and improve data structures that support modeling, analysis, and automation. • Work on improving the SOP driven experience by reducing manual steps and increasing automation. • Analyze complex datasets to identify patterns, trends, and opportunities for product value. • Continuously evaluate model performance and iterate to improve accuracy, reliability, and impact. • Ensure solutions are efficient, scalable, and aligned with real-world workflows and user needs.
• Experienced in applied data science, machine learning, or advanced analytics in a product-driven environment. • Strong foundation in statistics, modeling, and experimental design. • Hands-on with Python and common data science libraries. • Comfortable building and evaluating models that move into production. • Strong SQL skills and ability to work with large, complex datasets. • Able to translate ambiguous problems into structured, data-driven solutions. • Collaborative and comfortable working across engineering, product, and leadership teams.
• Competitive pay based on the market • Open to part-time or full-time work
Apply Now🕒 April 13
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