Product Intelligence & Data Analytics Manager
B
Baton (A Ryder Technology Lab)Logistics, Supply Chain SaaS
United StatesFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 3-5+ years
- Required Skills
- SQLMicrosoft Power BISnowflakeProduct Analytics
Requirements
- 3-5+ years of hands-on experience in product analytics within SaaS or technology-enabled environments.
- Strong ability to extract insights from product usage, engagement, activation, retention, and feature adoption data.
- Experience defining and maintaining KPI frameworks aligned to customer and business outcomes.
- Ability to translate complex product, data, and market signals into clear narratives and directional strategy.
- Can present findings to both technical and non-technical audiences, including executive stakeholders.
- Experience managing cross-functional stakeholders across Product, Engineering, Customer Success, and Sales.
- Ability to drive analysis projects from ambiguous problem definition through execution and delivery.
- Strong cross-functional influence without direct authority.
- Strong SQL proficiency with the ability to independently structure, clean, validate, and analyze data from multiple sources.
- Experience building and maintaining trusted dashboards in Power BI (or similar BI tools).
- Experience working within structured data warehouse environments and handling data across multiple systems (VoC, CRM, product usage platforms).
Responsibilities
- Own RyderShare product analytics end-to-end, including adoption, activation, retention, feature utilization, and operational effectiveness.
- Define and maintain core product KPIs aligned to customer value and business outcomes.
- Ensure KPI consistency, accuracy, and executive trust across dashboards and reporting layers.
- Partner with Product Managers to evaluate feature performance and inform roadmap prioritization using outcome-focused insights.
- Translate complex product usage, customer behavior, and market signals into clear narratives.
- Design and maintain executive-ready dashboards and structured insight narratives.
- Proactively surface risks, trends, opportunities, and recommended decisions.
- Tie product usage and adoption data to operational outcomes, customer health, renewals, and growth conversations.
- Synthesize quantitative analytics with Voice of Customer inputs and qualitative insights.
- Drive analysis projects from ambiguous problem definition through structured delivery.
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