Job details
About this role
Role overview
This is a senior product management role owning the strategy, roadmap, and delivery of a client-facing analytics and AI-powered insights product for enterprise SaaS customers. The position sits at the intersection of data, AI, and product craft, combining conversational analytics, embedded dashboards, and AI-accelerated workflows. It calls for someone technically credible who pairs a customer-first mindset with hands-on comfort using AI tools to ship both analytics features and faster product work.
Responsibilities
- Define and drive the product vision, strategy, and roadmap for a client-facing analytics and AI surface, balancing near-term delivery with long-term innovation. - Shape the end-to-end analytics experience for enterprise personas, including dashboards, reports, and insight narratives around supplier readiness, compliance, and risk. - Lead delivery of conversational analytics capabilities such as natural-language-to-insight, translating user questions into data-grounded answers. - Partner with data engineering, data science, and platform teams to evaluate and leverage AI infrastructure and LLM-backed tooling for analytics features. - Collaborate on semantic models and metrics layers, working with embedded visualization platforms to deliver insight-driven experiences. - Use AI tools and agents to accelerate personal PM workflows, including research, discovery synthesis, story drafting, and prototyping analytical use cases. - Coordinate with customer success, sales, and implementation teams to drive adoption and represent analytics capabilities to enterprise clients.
Requirements
- Approximately 5 years of product management experience owning shipped capabilities in a multi-tenant SaaS environment. - Bachelor's degree or higher in computer science, mathematics, engineering, statistics, data science, or equivalent practical depth. - Hands-on experience building and launching customer-facing analytics products (not only internal reporting tools). - Familiarity with analytics data infrastructure such as Snowflake or Databricks, including data models and semantic layers. - Working knowledge of AI and ML product concepts applied to analytics, including NLQ, conversational BI, or LLM integration patterns. - Ability to engage credibly with data engineers, analytics engineers, and ML engineers; technical depth strongly preferred. - Proficiency with roadmap and design tools (examples include Aha!, Jira, and Figma or equivalents).
Nice to have
- Exposure to B2B enterprise SaaS, supply chain, risk management, EHS/HSE, ESG, or workforce compliance domains. - Familiarity with LLM-backed analytical tooling applied to structured data queries. - Track record leading go-to-market product initiatives from discovery through launch and post-launch optimization.
Benefits and work setup
- Remote-friendly work setup as indicated by the listing. - Compensation includes a base salary range of approximately $87,500 to $180,000 per year, with potential bonus eligibility. - Benefits package includes health, dental, and vision insurance, a 401(k) plan, and paid time off.