Revenue Operations Analytics Lead, Americas

Copeland•St Louis, MO

3d•Hybrid

About The Position

We are seeking a strategic, highly analytical lead to build and scale commercial intelligence for the Americas. The Analytics Lead will establish trusted revenue metrics, generate executive-level insights, and help leaders make faster, data-driven commercial decisions. This role will own KPI governance, analytics strategy, performance visibility, and analytical AI use cases. Working closely with Sales Strategy & Operations and enterprise Analytics teams, the Analytics Lead will translate data into clear recommendations, while Sales Strategy & Operations leads the commercial response and execution.

Requirements

6+ years in Revenue Operations, Sales Operations, Commercial Analytics, or Business Analytics.
Experience with pipeline, performance, growth, and revenue metrics.
Experience managing or mentoring analysts.
Advanced Excel and experience with BI tools such as Sigma, Power BI, or Tableau.
Strong analytical problem-solving and data storytelling skills.
Ability to influence senior stakeholders through clear executive communication.
Ability to connect business priorities with technical teams and solutions.
Must be legally authorized to work in the United States. This is not a position for which sponsorship will be provided. Individuals with temporary visas such as E, F-1 with OPT or CPT, H-1, H-2, L-1, B, J or TN, or who need sponsorship for work authorization now or in the future, are not eligible for hire.

Nice To Haves

Experience working with Salesforce or another enterprise CRM platform
Experience building or scaling an analytics or commercial intelligence capability.
Exposure to predictive analytics, Generative AI tools, and automation.
Familiarity with SQL, data manipulation, data modeling, and analytics infrastructure.
Demonstrated success partnering with strategy and operations leaders to convert insights into action.

Responsibilities

Generate actionable insights: Translate business questions into structured analysis, scenarios, and recommendations.
Diagnose performance: Identify drivers of pipeline health, conversion, revenue growth, productivity, and performance gaps.
Influence decisions: Deliver executive-ready insights that guide commercial priorities and actions.
Measure impact: Evaluate implemented recommendations and identify where course correction is needed.
Ensure consistent metrics: Standardize pipeline, conversion, coverage, growth, and productivity KPIs.
Establish a trusted source of truth: Align definitions across systems and maintain the revenue KPI glossary.
Own the analytics product vision: Set priorities and requirements for dashboards, scorecards, and the broader reporting ecosystem.
Drive scalable delivery and adoption: Partner with BI and Data teams to translate requirements, validate outputs, and improve business use.
Set the use-case roadmap: Prioritize analytical AI opportunities in segmentation, opportunity identification, pipeline risk, forecasting, and scenario analysis.
Define business requirements: Translate commercial problems into requirements and validate outputs with Data and Analytics teams.
Drive adoption: Partner with Enablement and CRM teams on workflow integration, training, and change management for AI and automation solutions.
Lead and develop the team: Set priorities, coach analysts, and establish clear performance expectations.
Focus the work: Balance existing reporting products, ad hoc analysis, and strategic initiatives.
Raise analytical quality: Establish standards for data quality, analysis, storytelling, and stakeholder communication.
Align stakeholders: Partner across Sales, Marketing, Product Management, Finance, Enablement, BI, and Data Engineering.