Lyric
About Lyric
Why we built Lyric: supply chains are as critical & complex as ever → every day, large enterprises are faced with trillions of possibilities for their supply chain → powerful algorithms are required to optimize these supply chain decisions (i.e. AI) → large enterprises are unable to leverage supply chain AI at scale due to (a) the rigidity & limited scope of point solutions (“buy”) and (b) the immense investment required to develop in-house (“build”).......until now (cue dramatic music in the background)......
Enter Lyric: an enterprise AI platform for supply chains - when enterprises evaluate whether to buy or build decision-making engines for their supply chains, we provide the best of both worlds thanks to:
Our deep catalog of supply chain AI products that are available out-the-box to optimize networks, allocate inventory, schedule routes, plan fulfillment capacity, promise orders, propagate demand, build predictions, analyze scenarios, and much more (buy)
Our platform-first approach enables business & technical users end-to-end composability for supply chain decision science with no-code, their code, or even forking our code (build).
At Lyric we’re building a new era in supply chain, with the team best equipped to build it. We’ve been at the intersection of supply chain & algorithms for 20+ years, which led us to a deep conviction that global supply chains needed something like Lyric. We’re proud to say that since our inception in Dec. 2021, this conviction has now been validated many times over. This is thanks to our double-digit number of Fortune 500 Customers (Smurfit WestRock, Estee Lauder, Coca-Cola, Nike, and more) who are innovating on their own terms every day on Lyric. After an incredible 2024, we expect 2025 to be even more of a rocket ship, and we can’t wait to see what our current & future customers 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.
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.
Own the ML Roadmap: Define and prioritize product features and enhancements related to ML-based forecasting and prediction in the supply chain context.
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.
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.
Data-Driven Insights: Lead initiatives to incorporate predictive analytics into the Lyric Supply Chain Platform, enabling users to make proactive, data-informed decisions.
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.
Technical Collaboration: Coordinate with engineering teams to implement and scale machine learning models, ensuring high performance and reliability.
Performance Metrics: Define key success metrics for ML-driven features, monitor model performance, and optimize outcomes through ongoing iterations.
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.
Documentation & Reporting: Provide comprehensive documentation of ML models, forecasts, and analytical methods for internal teams and external stakeholders.
5+ years of product management experience, preferably in machine learning or data-driven product development.
Strong understanding of ML/AI techniques, especially in forecasting and predictive modeling, including regression models, time-series analysis, and demand forecasting.
Hands-on experience with data science tools (e.g., Python, R, SQL) and ML frameworks (e.g., TensorFlow, Scikit-learn).
Proven track record of launching and scaling ML/AI-based products, ideally in SaaS or enterprise environments.
Excellent ability to translate complex technical concepts into business outcomes and vice versa.
Strong analytical, problem-solving, and decision-making skills.
Experience with Agile methodologies and product lifecycle management tools (e.g., JIRA, Confluence).
Exceptional communication and stakeholder management skills, with a focus on driving alignment across cross-functional teams.
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.