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Manager, Revenue Operations and Scaled Services

Job in Hoboken, Hudson County, New Jersey, 07030, USA
Listing for: Walmart Inc.
Full Time position
Listed on 2026-11-01
Job specializations:
  • IT/Tech
    Data Analyst, Business Intelligence, Business Systems & Technology Analysis
  • Business
    Data Analyst, Business Intelligence, Business Systems & Technology Analysis
Salary/Wage Range or Industry Benchmark: 96000 - 186000 USD Yearly USD 96000.00 186000.00 YEAR
Job Description & How to Apply Below

This notice is being provided as a result of the filing of an Application for Permanent Alien Labor Certification. Any person may provide documentary evidence bearing on the application to the Certifying Officer of the Department of Labor: U.S. Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification, 200 Constitution Avenue, NW, Room N-5311, Washington, DC 20210

Position and

Job Location

Manager, Revenue Operations and Scaled Services

221 River Street, Hoboken, NJ 07030

Duties

Analyze and interpret multi-dimensional revenue signals and commercial data across Segment level business verticals to improve business efficiency within the SaaS Product Revenue Operations function, leveraging advanced analytical methodologies to translate pipeline indicators into actionable forecasting inputs. Develop and operationalize predictive and prescriptive Revenue Operations forecasting model solutions — including multi-segment customer lifecycle analysis— that meet business goals and drive commercial pipeline accuracy within go-to-market function.

Apply comprehensive understanding of the data ecosystem — including Data Management, Data Quality Standards, Data Governance, Accessibility, Storage, and Scalability — to architect Salesforce CRM pipeline hygiene and structural data validation frameworks, ensuring audit-ready, high-fidelity Revenue Operations reporting across commercial and business development pipelines. Use advanced knowledge in Data Discovery tools including Google Big Query, Data Lake, and SQL to write queries and analyze Revenue Operations data, identifying patterns, trends, outliers, and correlations across commercial datasets serving Commercial, Business Development, and Data partner teams.

Support the identification and application of statistical and machine learning techniques — including predictive and prescriptive modeling methodologies — based on business requirements, to develop and continuously refine multi-segment Revenue forecasting models and enable data-led commercial decision-making. Assist in the planning, design, and implementation of exploratory data analysis and Revenue Operations analytics research projects, contributing to the establishment and continuous maturation of an AI/ML-integrated analytics foundation in partnership with the Data Foundations team.

Translate business requirements into projects, activities, and tasks aligned to the overall Revenue Operations strategy and domain-specific commercial roadmap, including strategic tool integration initiatives for Marketo, Gong, and Salesforce, and developing scalable analytical artifacts supporting Canada and Mexico geographic market expansion. Define, design, and implement Revenue Operations-exclusive Key Performance Indicators and automated reporting pipelines using Tableau, Power BI, and Salesforce Analytics, replacing manual reporting workflows with self-service, real-time dashboards that track and convey KPIs including ARR growth, Deal Win Rate, Churn Rate, and Business Development Pipeline velocity to empower data-driven business and commercial decisions.

Present to and influence cross-functional teams and senior business stakeholders using Tableau, Power BI, and Salesforce-integrated visualization frameworks, conveying clear and precise Revenue Operations performance narratives and commercial pipeline insights through audience-appropriate data storytelling and business communication. Conduct comprehensive Salesforce ERP data analysis by integrating financial, operational, and commercial datasets across enterprise resource planning modules, leveraging Salesforce reporting objects and custom data objects to surface cross-functional revenue insights and support…

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