Product Intelligence & Data Analytics Manager

Baton (A Ryder Technology Lab)

9h•Remote

About The Position

We are seeking a Product Intelligence & Data Analytics Manager who will own product analytics, KPI frameworks, and executive-ready insight generation across RyderShare and related technology products. This role sits at the intersection of Product, Engineering, Customer Success, and Sales Enablement - translating product usage data, Voice of Customer inputs, and competitive signals into structured narratives, measurable KPIs, and clear business decisions. This is an insight ownership role. You will define what we measure, how we measure it, and how we translate insight into action.

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.
Moves stakeholders beyond descriptive reporting toward recommended actions.
Demonstrated ability to ramp quickly on new domains and complex industries.
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 (including Snowflake or similar cloud data warehouses).
Experience building and maintaining trusted dashboards in Power BI (or similar BI tools), ensuring KPI accuracy and consistency across reporting layers.
Experience working within structured data warehouse environments and handling data across multiple systems (VoC, CRM, product usage platforms).

Nice To Haves

5-8+ years in product analytics, business intelligence, or data analytics within SaaS or technology-enabled environments.
Experience synthesizing quantitative product analytics with Voice of Customer (VoC), customer feedback, and qualitative market signals.
Experience contributing to competitive positioning, differentiation analysis, or market intelligence initiatives.
Background in B2B enterprise SaaS, logistics, freight, supply chain, or operationally complex platforms.
Experience operating within organizations with established analytics maturity and standardized KPI frameworks.
Exposure to cross-functional enablement work supporting Customer Success, Sales, and executive teams.

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 explaining what is happening, why it matters, and what to do next.
Move stakeholders beyond descriptive reporting toward recommended actions.
Design and maintain executive-ready dashboards and structured insight narratives.
Proactively surface risks, trends, opportunities, and recommended decisions across product and customer performance.
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.
Maintain visibility into competitive dynamics and identify differentiation opportunities or risk areas.
Provide account-level and market-level analysis to support cross-functional decision-making.
Drive analysis projects from ambiguous problem definition through structured delivery.
Influence Product, Engineering, Customer Success, and Sales without direct authority.
Build and scale a structured Product Intelligence capability within Customer Success Enablement.