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.

Requirements

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 background strongly preferred over a Sales or Marketing PM path.
Active user of AI tools in day-to-day work, whether for research, writing, analysis, or workflow acceleration; comfortable experimenting with and applying new AI capabilities.
Proficiency with Aha!, Jira, and Figma (or directly equivalent tools) for roadmap management, backlog execution, and design collaboration.
Strong analytical and data literacy; excellent written and verbal communication across technical and executive audiences.
Familiarity with Snowflake Cortex, Cortex Analyst, or similar LLM-backed analytical tooling applied to structured data query and insight generation.
Experience with B2B enterprise SaaS, supply chain, risk management, EHS/HSE, ESG, or workforce compliance is a meaningful plus.
Track record of leading go-to-market product initiatives from discovery through GA launch and post-launch optimization.

Benefits

health, dental and vision insurance
401(k)
PTO

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Product ManagementAnalyticsData InfrastructureData ModelsSemantic LayersAI ConceptsMachine LearningNatural Language Query (NLQ)Embedded AnalyticsCustomer-facing Products

Soft Skills

Analytical SkillsData LiteracyCommunication SkillsCollaborationStakeholder EngagementProblem SolvingInnovationStrategic ThinkingLeadershipAdaptability