Senior Product Manager

Company Description Daybreak is a leading provider of AI-powered solutions revolutionizing the supply chain planning industry. Their AI Prediction Platform, AI Decision System, and digital planning colleague, Luma, empower companies to move beyond legacy systems and achieve unparalleled accuracy, efficiency, and agility in their operations. Role Description This is a full-time remote role for a Senior Product Manager at Daybreak. The Senior Product Manager will be responsible for overseeing the development and management of AI-powered supply chain planning solutions. They will collaborate with cross-functional teams, define product strategies, prioritize features, and drive product initiatives to meet business goals. Qualifications

• 4-6 years in Product Management, Business Analysis, AI Technology, and Supply Chain Planning expertise((e.g. demand forecasting, inventory management).
• Bachelor's degree in Business, Engineering, Computer Science, or a related field
• Hands-on experience with time-series ML models (e.g., ARIMA, AutoGluon, Nixtla, or similar).
• Exposure to Databricks or similar platforms for managing large-scale data pipelines is an added advantage.
• Skills:
• Experience in defining product strategies and driving product initiatives
• Strong analytical and problem-solving skills,detail-oriented and proactive in identifying opportunities for platform improvements.
• Excellent communication and leadership skills
• Ability to work collaboratively in cross-functional teams
• Customer-first approach with a passion for solving real-world forecasting challenges.
• Proficiency in agile tools like Jira and Confluence.
• Basic understanding of AI/ML workflows and forecasting evaluation metrics.
• Collaborative and curious, eager to learn about supply chain planning and emerging forecasting technologies.
• Bachelor's degree in Business, Engineering, Computer Science, or a related field

1. Platform Ownership :

• Lead the development and implementation of time-series forecasting features within the Prediction Platform.
• Manage the product backlog, ensuring alignment with business goals and customer requirements.
• Validate platform functionality through UAT and provide iterative feedback to engineering teams.
• Focus on scalability and accuracy, ensuring the platform supports large-scale forecasting needs.

1. Documentation & Enablement :

• Develop and maintain detailed documentation, including feature overviews, workflows, and release notes.
• Create training materials to onboard Customer Success (CS) teams, partners, and customers on forecasting workflows.
• Maintain a well-organized repository for all platform-related documentation to support internal and external users.

1. Customer Success & Feedback Integration :

• Work closely with CS teams to gather customer feedback and translate it into actionable product improvements.
• Identify pain points in forecasting workflows and collaborate with engineering to resolve them.
• Support onboarding efforts by ensuring environments and tools are ready for use by customers and partners.

1. Go-To-Market (GTM) Support :

• Build and maintain demo environments and datasets to showcase the platform’s forecasting capabilities.
• Define clear workflows and use cases for sales teams to articulate the platform’s value in supply chain planning contexts.
• Assist in creating dashboards and reports to demonstrate forecast accuracy and impact.

1. Cross-Functional Collaboration :

• Partner with engineering and QA teams to integrate time-series ML models and ensure high-quality implementations.
• Collaborate with the R&D team to incorporate advancements in AI/ML forecasting techniques.
• Align with supply chain SMEs and Decision Platform teams to ensure cohesive workflows across platforms.
• Work with Databricks engineers to optimize data workflows and streamline model training pipelines.