Manager, Product Management

o9 Solutions, Inc.•Dallas, TX

1d•Hybrid

About The Position

At o9, our mission is to be the Most Value-Creating Platform for enterprises by transforming decision-making through our AI-first approach. By integrating siloed planning capabilities and capturing millions—even billions—in value leakage, we help businesses plan smarter and faster. This not only enhances operational efficiency but also reduces waste, leading to better outcomes for both businesses and the planet. Global leaders like Google, PepsiCo, Walmart, T-Mobile, AB InBev, and Starbucks trust o9 to optimize their supply chains. POSITION: Manager, Product Management LOCATION: 1501 Lyndon B Johnson Fwy, Ste 140, Dallas, TX 75234 [and various unanticipated locations throughout the U.S.; may telecommute/work from home] Manager, Product Management needed by o9 Solutions, Inc. in Dallas, TX [and various unanticipated locations throughout the U.S.; may telecommute] to Act as the key liaison between business stakeholders and technical teams to ensure alignment of product features with strategic objectives and customer needs. Collaborate with leadership to validate that proposed features deliver measurable business value, maintaining high standards for quality, scalability, and readiness. Lead structured requirements gathering through meetings, workshops, and documentation reviews. Translate business needs into actionable, technically feasible product concepts, authoring functional specs, user stories, and acceptance criteria. Develop prototypes, use cases, and design data visualizations to support usability testing and performance communication. Apply analytics, modeling, and optimization to inform decisions. Drive Agile product delivery by collaborating with engineering, data science, and implementation teams on release plans, backlog prioritization, and sprint execution. Own the product roadmap and ensure timely, iterative feature delivery through stakeholder engagement and performance-driven enhancements. Design and execute test plans to validate workflows and analytical models, ensuring robustness across business scenarios. Coordinate issue resolution, define automated testing protocols, and manage regression testing. Package final solutions with training content, release notes, and technical documentation. Conduct product demos, workshops, and training to support adoption and ensure long-term success. Promote continuous innovation by monitoring market trends, user behavior, and product performance. Champion data-driven decisionmaking and foster cross-functional collaboration to evolve the product and exceed expectations. Serve as a subject matter expert throughout the product lifecycle, driving sustainable value and customer satisfaction. Utilize machine learning, optimization algorithms, statistics, and large-scale system modeling. Utilize Python and relevant libraries (NumPy, scikit-learn, LightGBM), as well as SQL for data manipulation and performance tuning. Use Spark, Databricks, and scalable data processing frameworks. Apply Large Language Models (LLMs) and deep learning frameworks such as PyTorch or TensorFlow. Design and manage machine learning pipelines including feature engineering, model tuning, and validation. Use analytical, statistical, and data visualization skills (Power BI/Tableau). 20% domestic travel required.

Requirements

Requires a Master’s degree, or foreign equivalent degree in Industrial Engineering, Operations Research, or Engineering Management.
Requires experience, course work and/or project experience in utilizing machine learning, optimization algorithms, statistics, and large-scale system modeling
Requires experience, course work and/or project experience in utilizing Python and relevant libraries (NumPy, scikit-learn, LightGBM), as well as SQL for data manipulation and performance tuning
Requires experience, course work and/or project experience in using Spark, Databricks, and scalable data processing frameworks
Requires experience, course work and/or project experience in applying Large Language Models (LLMs) and deep learning frameworks such as PyTorch or TensorFlow
Requires experience, course work and/or project experience in designing and managing machine learning pipelines including feature engineering, model tuning, and validation
Requires experience, course work and/or project experience in using analytical, statistical, and data visualization skills (Power BI/Tableau).

Responsibilities

Act as the key liaison between business stakeholders and technical teams to ensure alignment of product features with strategic objectives and customer needs.
Collaborate with leadership to validate that proposed features deliver measurable business value, maintaining high standards for quality, scalability, and readiness.
Lead structured requirements gathering through meetings, workshops, and documentation reviews.
Translate business needs into actionable, technically feasible product concepts, authoring functional specs, user stories, and acceptance criteria.
Develop prototypes, use cases, and design data visualizations to support usability testing and performance communication.
Apply analytics, modeling, and optimization to inform decisions.
Drive Agile product delivery by collaborating with engineering, data science, and implementation teams on release plans, backlog prioritization, and sprint execution.
Own the product roadmap and ensure timely, iterative feature delivery through stakeholder engagement and performance-driven enhancements.
Design and execute test plans to validate workflows and analytical models, ensuring robustness across business scenarios.
Coordinate issue resolution, define automated testing protocols, and manage regression testing.
Package final solutions with training content, release notes, and technical documentation.
Conduct product demos, workshops, and training to support adoption and ensure long-term success.
Promote continuous innovation by monitoring market trends, user behavior, and product performance.
Champion data-driven decisionmaking and foster cross-functional collaboration to evolve the product and exceed expectations.
Serve as a subject matter expert throughout the product lifecycle, driving sustainable value and customer satisfaction.
Utilize machine learning, optimization algorithms, statistics, and large-scale system modeling.
Utilize Python and relevant libraries (NumPy, scikit-learn, LightGBM), as well as SQL for data manipulation and performance tuning.
Use Spark, Databricks, and scalable data processing frameworks.
Apply Large Language Models (LLMs) and deep learning frameworks such as PyTorch or TensorFlow.
Design and manage machine learning pipelines including feature engineering, model tuning, and validation.
Use analytical, statistical, and data visualization skills (Power BI/Tableau).