Sr. Technical Product Manager - Analytics and Measurement (AI)

Location: Remote, United States, with approximately 10% in-person collaboration; external candidates may need to attend an in-person interview at a hirify.global location.

Company

hirify.global is a media and entertainment business operating brands across news, business, golf, sports, and genre entertainment, including Fandango and other digital assets.

What you will do

• Own the roadmap, backlog, and delivery for Studio and Exhibitor analytics, measurement, dashboards, reports, and self-service experiences.
• Work with Studio and Exhibitor users and customer-facing teams to define KPIs, calculations, comparisons, reporting requirements, and acceptance criteria.
• Shape chat and agentic analytics experiences by defining answerable questions, metric logic, data context, tools, and workflows.
• Execute client-side tag placements, changes, removals, and validation in Adobe and Google Analytics environments, and support server-to-server CAPI measurement solutions.
• Use SQL and AI-assisted or agentic workflows to create metric logic, queries, dashboard and report prototypes, and recurring analysis from approved datasets; validate calculations, source data, edge cases, and answer quality.
• Prototype and configure dashboards and reports with AWS analytics and AI services, including Amazon Quick Suite, Quick Sight, and Amazon Bedrock AgentCore, as well as Omni, Tableau, or ChatGPT; track accuracy, adoption, usability, documentation, and access controls while partnering with BI, Data Science, Data Engineering, UX, and Engineering.

Requirements

• 6+ years of experience in product management, BI, analytics, or data products, including analytics used by customers or business teams.
• Strong SQL and data fluency, including joins, grain, aggregations, metric definitions, reporting logic, and investigating unexpected results.
• Hands-on experience building or configuring dashboards, reports, or analytics views in Amazon Quick Suite, Quick Sight, Omni, Tableau, Looker, Superset, or similar tools.
• Practical experience using generative AI and agentic workflows to produce analytics, including queries, metrics, dashboards, reports, or natural-language data answers.
• Ability to test AI-generated analysis for calculation accuracy, explainability, data permissions, and consistency with agreed metric definitions.
• Understanding of event tracking, measurement tags or pixels, and conversion measurement.
• Clear communication and prioritization across product, data, and engineering teams.

Nice to have

• Experience with server-to-server APIs.

Culture & Benefits

• Remote-first flexibility with opportunities for in-person collaboration.
• Collaborative, cross-functional work with product, engineering, marketing, analytics, and technical partners.
• Emphasis on trust, accuracy, reliability, integrity, transparency, teamwork, agility, and entrepreneurial initiative.
• Opportunity to work with modern BI tools and AI-enabled analytics capabilities.
• Competitive compensation, comprehensive benefits, and opportunities for growth.