Product Manager Analytics & AI
Avetta, LLC
| Company | Avetta, LLC |
| Category | Data & Analytics |
| Location | US - Remote |
| Remote | Remote |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 16 Apr 2026 |
| Last verified | 3 Aug 2026 |
| Source | Employer ATS (greenhouse) |
Description
SUMMARY
Avetta is building the largest global community of hiring clients and suppliers that are Ready to Work. Its unified platform streamlines compliance, prequalification, safety and performance benchmarking in a single, integrated experience. Trusted by 360,000 businesses across more than 120 countries, Avetta blends AI-driven insights and human expertise to close risk gaps and strengthen supplier reliability so projects start on time, risks are managed proactively and operations scale with certainty.
We are looking for a Product Manager, Analytics & AI to own the strategy, roadmap, and execution of Avetta's client-facing analytics and AI-powered insights capabilities. The ideal candidate brings technical credibility, a customer-first mindset, and the comfort to use AI tools to accelerate their own PM craft, not just to ship AI features.
ESSENTIAL DUTIES AND RESPONSIBILITIES:
Own the product vision, strategy, and roadmap for Avetta's Analytics & AI surface, balancing near-term delivery with long-term innovation, and representing the area in PI planning and cross-team dependency management.
Drive the end-to-end client-facing analytics experience for enterprise hiring client personas: the dashboards, reports, and insights that make supplier readiness, risk, and compliance visible and actionable.
Define and deliver Avetta's conversational analytics capabilities, including; NLQ to Insight, using natural language questions that return direct, data-grounded answers about supplier readiness, compliance, and risk.
Partner with Data Engineering, Data Science, and Platform teams to evaluate and leverage AI infrastructure, including Snowflake Cortex capabilities or equivalent, to power conversational and generative analytics features.
Serve as the product interface to analytics infrastructure teams, shaping semantic models and metrics layers; work with embedded visualization tooling (Sisense, Tableau, Qlik, or equivalent) to deliver insight-driven experiences within the Avetta platform.
Leverage AI tools and agents to accelerate your own PM work, including conducting market and competitive research, drafting solution capability narratives, synthesizing customer discovery findings, generating user story frameworks, and prototyping analytical use cases.
Collaborate with the Analytics PO for refinement and sprint planning for the Analytics & AI scrum team using Aha! for roadmap and initiative planning, Jira for backlog and sprint management, and Figma for UX collaboration and design review.
Partner with Customer Success, Sales, and Implementation teams to drive analytics adoption, surface product-market insights, and represent Avetta's Analytics & AI capabilities to enterprise clients.
PREFERRED QUALIFICATIONS, IDEAL EDUCATION AND TRAINING:
5 years of Product Management experience with demonstrated ownership of shipped product capabilities in a multi-tenant SaaS environment.
Bachelor's degree or higher in Computer Science, Mathematics, Engineering, Statistics, Data Science, or equivalent; candidates with demonstrated technical depth and equivalent experience will be considered.
Hands-on product experience building and launching customer-facing analytics products. Candidates whose analytics experience is limited to internal reporting tools without client-facing product ownership are not a strong match.
Experience working with analytics data infrastructure (Snowflake, Databricks, or equivalent) in a product capacity, including understanding of data models and semantic layers.
Experience delivering embedded analytics experiences using visualization platforms such as Sisense, Tableau, Qlik, Looker, or equivalent.
Working knowledge of AI and ML product concepts applied to analytics: NLQ, conversational BI, LLM integration patterns, or AI-powered insight generation.
Demonstrated ability to engage credibly with data engineers, analytics engineers, and ML engineers; technical back