Manager, Revenue Operations and Scaled Services

Walmart•Hoboken, NJ

12d•$96,000 - $186,000

About The Position

The Manager, Revenue Operations and Scaled Services analyzes multi-dimensional revenue signals and commercial data across business segments to improve efficiency and forecasting accuracy within SaaS Product Revenue Operations. The role develops and operationalizes predictive and prescriptive forecasting models, including multi-segment customer lifecycle analysis, and applies statistical and machine learning methods to support commercial decision-making. The position works across the data ecosystem to establish Salesforce CRM pipeline hygiene and data validation frameworks, and uses Google BigQuery, Data Lake, and SQL to explore and analyze revenue operations data. It also contributes to exploratory research and the development of an AI/ML-integrated analytics foundation with the Data Foundations team. The manager translates business requirements into projects aligned with the Revenue Operations strategy, including Marketo, Gong, and Salesforce tool integration and analytical support for expansion into Canada and Mexico. The role develops exclusive KPIs and automated reporting pipelines using Tableau, Power BI, and Salesforce Analytics, replacing manual workflows with self-service dashboards. It presents performance narratives and pipeline insights to cross-functional teams and senior stakeholders, analyzes Salesforce ERP data across financial, operational, and commercial domains, and applies advanced analytics and generative AI to reduce manual reporting effort and improve forecasting accuracy.

Requirements

Master’s degree or equivalent in Business, Marketing, Communication, Digital Media/Advertising, Engineering (any), or a related area; alternatively, 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 tools adoption and analytics, and data-source automation and scheduling scripts.
Experience assessing 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 and extrapolating impacts of annual seasonality events, including generating correlations with marketplace seller data and relevant business metrics.
Experience analyzing trends, seasonality, drivers, and root causes to calibrate forecasting and capacity planning and provide recommendations to business teams.
Experience communicating cross-functionally about Business Development Pipeline and CRM insights using charts, presentations, and self-service dashboards for business and technical stakeholders.
Experience generating automated database-driven dashboards and mining data related to data management, data quality, Annual Recurring Revenue, Deal Win Rate, and Churn Rate, with results prepared for Tableau, MS Power BI, and Looker.
Experience using advanced MS Excel, including macros, large datasets, charts, pivot tables, VLOOKUPs, linear regression, and ETS.
Experience with 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 forecasting inputs.
Develop and operationalize predictive and prescriptive Revenue Operations forecasting models, including multi-segment customer lifecycle analysis.
Apply data management, quality, governance, accessibility, storage, and scalability principles to Salesforce CRM pipeline hygiene and data validation frameworks.
Use Google BigQuery, Data Lake, and SQL to query and analyze commercial and Revenue Operations data, identifying patterns, trends, outliers, and correlations.
Support the selection and application of statistical and machine learning techniques to develop and refine multi-segment revenue forecasting models.
Assist with planning, designing, and implementing exploratory data analysis and Revenue Operations analytics research projects with the Data Foundations team.
Translate business requirements into projects, activities, and tasks aligned with the Revenue Operations strategy and commercial roadmap.
Support strategic integration of Marketo, Gong, and Salesforce tools and develop scalable analytical artifacts for Canada and Mexico market expansion.
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 KPIs 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 visualizations and storytelling.
Analyze Salesforce ERP data by integrating financial, operational, and commercial datasets and using Salesforce reporting and custom data objects to surface revenue insights.
Apply advanced analytics tools, including generative AI applications such as ChatGPT and native AI models, to automate Revenue Operations reporting, reduce manual effort, and improve forecasting accuracy.