About the company
Why We Built Lyric: Supply chains are more critical and complex than ever. Every day, large enterprises navigate trillions of possible decisions, requiring powerful algorithms—AI—to optimize their supply chain operations. Yet, most organizations struggle to leverage supply chain AI at scale. Traditional solutions present two flawed choices:
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Buying off-the-shelf point solutions, which are rigid and limited in scope.
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Building AI capabilities in-house, which demands immense investment and expertise.
That is—until now. (Cue dramatic music.)
Enter Lyric: Lyric is an enterprise AI platform built specifically for supply chains, offering the best of both worlds when companies weigh the decision to buy or build:
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Out-of-the-box AI solutions for optimizing networks, allocating inventory, scheduling routes, planning fulfillment capacity, promising orders, propagating demand, building predictions, analyzing scenarios, and more. (Buy)
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A platform-first approach that empowers both business and technical users with end-to-end composability—leveraging no-code tools, their own code, or even forking our code to build and refine decision intelligence. (Build)
With Lyric, enterprises no longer have to choose between flexibility and speed—they get both.
The Mission: We’re building a new era in supply chain with the team best equipped to lead it. With over 20 years at the intersection of supply chain and algorithms, we developed a deep conviction that global supply chains needed something like Lyric. Since our inception in December 2021, that conviction has been validated time and time again.
Today, a growing number of Fortune 500 companies—including Smurfit WestRock, Estée Lauder, Coca-Cola, Nike, and more—are innovating on their own terms with Lyric. After an incredible 2024, we expect 2025 to be an even bigger rocket ship, and we can’t wait to see what our customers—both current and future—are empowered to build with us next.
We are looking for a dynamic and driven Machine Learning Product Owner who will be instrumental in shaping the future of our supply chain platform by building robust Forecasting and Prediction capabilities. You’ll work at the intersection of data science, product management, and supply chain expertise to design and implement solutions that predict demand, forecast inventory needs, and optimize supply chain operations.
Role Overview:
As the ML Product Owner at Lyric, you will lead the development of machine learning models and forecasting tools that provide predictive insights to our supply chain platform. You will collaborate with cross-functional teams, including data scientists, engineers, and supply chain experts, to identify business needs and drive product innovations. Your main goal will be to leverage ML/AI technologies to improve forecasting accuracy, reduce risks, and enhance decision-making processes for our customers.
Key Responsibilities:
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Own the ML Roadmap: Define and prioritize product features and enhancements related to ML-based forecasting and prediction in the supply chain context.
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Bridge Business and Technology: Collaborate with stakeholders across Lyric, including business leaders, customers, data scientists, and engineers, to understand needs and translate them into scalable ML solutions.
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Forecasting & Predictive Modeling: Work with the data science team to design, implement, and refine machine learning models that predict demand, optimize inventory levels, and forecast supply chain disruptions.
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Data-Driven Insights: Lead initiatives to incorporate predictive analytics into the Lyric Supply Chain Platform, enabling users to make proactive, data-informed decisions.
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User-Centric Design: Ensure the ML features are intuitive, actionable, and seamlessly integrated into the existing platform. Drive customer feedback loops to continuously refine the forecasting tools.
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Technical Collaboration: Coordinate with engineering teams to implement and scale machine learning models, ensuring high performance and reliability.
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Performance Metrics: Define key success metrics for ML-driven features, monitor model performance, and optimize outcomes through ongoing iterations.
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Stay Ahead of Trends: Keep up-to-date with the latest trends and developments in machine learning, AI, and supply chain management to identify new opportunities for innovation.
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Documentation & Reporting: Provide comprehensive documentation of ML models, forecasts, and analytical methods for internal teams and external stakeholders.
Qualifications:
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5+ years of product management experience, preferably in machine learning or data-driven product development.
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Strong understanding of ML/AI techniques, especially in forecasting and predictive modeling, including regression models, time-series analysis, and demand forecasting.
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Hands-on experience with data science tools (e.g., Python, R, SQL) and ML frameworks (e.g., TensorFlow, Scikit-learn).
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Proven track record of launching and scaling ML/AI-based products, ideally in SaaS or enterprise environments.
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Excellent ability to translate complex technical concepts into business outcomes and vice versa.
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Strong analytical, problem-solving, and decision-making skills.
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Experience with Agile methodologies and product lifecycle management tools (e.g., JIRA, Confluence).
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Exceptional communication and stakeholder management skills, with a focus on driving alignment across cross-functional teams.
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Bachelor's or Master’s degree in a technical field such as Computer Science, Engineering, Data Science, or a related discipline. An MBA or relevant business experience is a plus.
