The role involves building and maintaining machine learning inference pipelines and model-serving workflows to support product matching and classification. You will collaborate with science and engineering teams to operationalize models, analyze performance, and improve model explainability.
Build, maintain, and optimize scalable data pipelines to support machine learning workflows, model inference, and business reporting. Collaborate with data scientists and ML engineers to ensure high-quality, clean datasets are available for training and evaluation.
Own the product strategy, roadmap, and end-to-end delivery of competitive intelligence capabilities including data collection and product matching. Partner with engineering and data science teams to develop scalable DaaS offerings and establish success metrics for data quality and customer adoption.
Own the strategy, roadmap, and delivery of foundational data platform capabilities supporting analytics, reporting, and AI/ML solutions. Define backend data requirements and drive data quality, governance, accessibility, performance, scalability, and cost efficiency in partnership with engineering, data science, analytics, and product teams.
Own the product strategy, roadmap, and end-to-end delivery of Trade Fund Optimization and Vendor Portal solutions. Collaborate with Engineering, Data Science, and UX teams to translate complex business needs into scalable product solutions.
