product
Posted Apr 3Product Manager for Data Science
Seattle, United StatesOn-site
Responsibilities
- Own the product vision and roadmap for our ML Platform, ensuring teams can easily experiment, train, deploy, and monitor models at scale.
- Drive adoption of modern AI tooling (e.g., vector stores, LLM orchestration frameworks, GPU-based training environments).
- Define SLAs, performance metrics, and developer
- Lead the strategy for transforming raw data into structured, high-quality, and meaningful assets that power insight-driven product features such as competitive benchmarking, performance diagnostics, and opportunity identification.
- Define and evolve the data models, taxonomies, and semantic layers that make data consistent, interpretable, and ready for analysis.
- Identify and prioritize high-value machine learning applications — such as recommendation systems, search relevance, anomaly detection, forecasting, and LLM-powered insights.
- Collaborate with business and engineering teams to bring ML models into production — ensuring performance, interpretability, and ethical AI practices.
- Own success metrics (e.g., model ROI, adoption, latency, accuracy) and establish iteration loops with DS teams. Strategy & Leadership
- Define the long-term strategy for AI/ML as a product capability — balancing foundational investments with applied innovation.
- Champion best practices for experimentation, responsible AI, and data-driven decision making.
- Influence executive stakeholders through clear storytelling, value framing, and impact What You Bring:
Requirements
- We are looking for a Senior Product Manager (PM) to drive strategy and execution across our data science and AI ecosystem — from the machine learning platform and data foundations to applied ML and AI-powered products that deliver measurable business impact.
- This is a pivotal role at the intersection of data science, machine learning engineering, and product strategy. You’ll partner with data scientists, ML engineers, data engineers, and business leaders to define and deliver the capabilities that enable our teams to develop, deploy, and scale AI-driven insights and automation across the company. What You'll Do:
- ML Platform & Infrastructure
- Applied ML & AI Use Cases
- Partner with senior leadership to align the ML roadmap with company priorities and data maturity.