Manager, Revenue Operations and Scaled Services

Walmart•Hoboken, NJ

11d

About The Position

The Manager, Revenue Operations and Scaled Services analyzes revenue signals and commercial data across business segments to improve SaaS Product Revenue Operations and forecasting accuracy. The role develops predictive and prescriptive forecasting models, including multi-segment customer lifecycle analysis, and applies data management, quality, governance, accessibility, storage, and scalability practices to maintain clean Salesforce CRM pipelines and reliable reporting. The position uses Google BigQuery, Data Lake, SQL, Salesforce, and other analytics tools to explore commercial datasets, identify trends and outliers, and support business, commercial, and data teams. It contributes to analytics research and the development of an AI/ML-integrated analytics foundation, translates business needs into projects and tool integrations, and supports market expansion in Canada and Mexico. The role designs Revenue Operations KPIs and automated reporting pipelines using Tableau, Power BI, Salesforce Analytics, and related tools. It replaces manual reporting with self-service dashboards, communicates performance insights to senior stakeholders, integrates financial, operational, and commercial data for strategic planning, and applies advanced analytics and generative AI to automate reporting and improve forecasting across the customer commercial lifecycle.

Requirements

Master’s degree or equivalent in Business, Marketing, Communication, Digital Media/Advertising, Engineering (any), or a related area; or a bachelor’s degree or equivalent in one of these areas and 2 years of experience in campaign management, business development, market development, or a related area.
Experience with forecasting and Revenue Operations modeling using exponential triple smoothing, weighted moving average, linear regression, and Python Prophet for demand planning and daily, weekly, monthly, and fiscal volume analytics and forecasting.
Experience using Google BigQuery and Trino SQL for exploratory data analysis involving Data Lake, Salesforce, new tool adoption and analytics, and data-source automation and scheduling scripts.
Experience evaluating business metrics and KPIs, including mean absolute percent error, day-of-week distribution, statistical significance, and power analysis.
Experience planning and executing hybrid forecasting strategies using predictive analytics and A/B testing to measure performance.
Experience configuring and analyzing what-if scenarios, extrapolating impacts of annual seasonality events, and correlating results with marketplace seller data and relevant business metrics.
Experience analyzing trends, seasonality, drivers, and root-cause complexities to calibrate forecasting and capacity planning and provide business recommendations.
Experience communicating Business Development Pipeline and CRM insights to cross-functional stakeholders through charts, presentations, and self-service dashboards.
Experience generating automated database-based dashboards and data-mining results relating to data management, data quality, Annual Recurring Revenue, and Deal Win Rate, and preparing data tables for Tableau, MS Power BI, and Looker.
Experience using advanced MS Excel, including macros, charts, pivot tables, Vlookups, linear regression, and ETS.
Experience with WMA, linear regression, Python Prophet forecasting, prescriptive analytics, generative AI, ChatGPT, Revenue Operations, multi-segment forecasting, and customer lifecycle analysis.
The employer will accept any amount of experience with the required skills.

Responsibilities

Analyze multi-dimensional revenue signals and commercial data across business segments to improve business efficiency and translate pipeline indicators into actionable forecasting inputs.
Develop and operationalize predictive and prescriptive Revenue Operations forecasting models, including multi-segment customer lifecycle analysis.
Apply data management, data quality, governance, accessibility, storage, and scalability practices to architect Salesforce CRM pipeline hygiene and data validation frameworks.
Use Google BigQuery, Data Lake, and SQL to query and analyze Revenue Operations data, identifying patterns, trends, outliers, and correlations.
Support the selection and application of statistical and machine learning techniques to develop and refine revenue forecasting models.
Assist with planning, designing, and implementing exploratory data analysis and Revenue Operations analytics research projects in partnership with the Data Foundations team.
Translate business requirements into projects and tasks aligned with the Revenue Operations strategy and commercial roadmap, including integrations for Marketo, Gong, and Salesforce.
Develop scalable analytical artifacts supporting geographic market expansion in Canada and Mexico.
Define and implement Revenue Operations KPIs and automated reporting pipelines using Tableau, Power BI, and Salesforce Analytics.
Replace manual reporting workflows with self-service, real-time dashboards tracking metrics such as ARR growth, Deal Win Rate, Churn Rate, and Business Development Pipeline velocity.
Present Revenue Operations performance narratives and commercial pipeline insights to cross-functional teams and senior stakeholders using appropriate data storytelling and visualization.
Analyze Salesforce ERP data by integrating financial, operational, and commercial datasets and using Salesforce reporting objects and custom data objects to support strategic leadership planning.
Apply advanced analytics tools, including generative AI applications such as ChatGPT and Native AI Models, to automate Revenue Operations and reduce manual reporting effort while improving forecasting accuracy.