Staff Product Manager – Finance Technology

Walmart•Bentonville, AR

7d•Onsite

About The Position

The Staff Product Manager – Finance Technology will lead product development for enterprise financial forecasting platforms that generate machine-learning-based forecasts for metrics such as net sales, merchandise sales, operational units, and fulfilled orders across base, merchandise, and marketplace channels. The role translates requirements from Finance, Merchandising, and Operations into scalable product specifications and manages forecast outputs across metric, channel, department, and category hierarchies, ensuring consistency and reconciliation across more than 60 departments and 2,000 categories. The role partners with data science teams to define machine-learning model requirements, including input signals, outputs, validation frameworks, and feedback loops. It also designs and maintains channel-mapping logic; aligns stakeholders and forecasts with planning cycles and operational workflows; and develops quantitative frameworks to assess forecast accuracy, financial impact, and return on investment. The position drives the transition from manual Excel-based forecasting and reporting to automated, governed systems that improve scalability, auditability, and consistency in enterprise financial and operational planning. The position is located at 811 Excellence Dr, Bentonville, AR 72716. The employer requires a master’s degree or equivalent in computer science, engineering, or a related field plus one year of product management or related experience, or a bachelor’s degree or equivalent in one of those fields plus three years of such experience. The employer will accept any amount of experience with the required skills.

Requirements

Master’s degree or equivalent in computer science, engineering, or a related field and at least one year of product management or related experience; OR a bachelor’s degree or equivalent in one of these fields and at least three years of product management or related experience.
Experience developing data-driven financial and operational decision-support systems, defining product strategy, and translating business needs into scalable product solutions.
Experience gathering requirements from Finance, Merchandising, and Operations and translating complex needs into product specifications, workflows, and analytical outputs.
Experience collaborating with data science and machine-learning teams on model inputs, outputs, feature engineering, evaluation metrics, and validation frameworks.
Experience applying forecasting concepts and analytical decision-support systems to financial planning, performance tracking, and business decision-making.
Experience managing cross-functional stakeholders across finance, operations, merchandising, engineering, and analytics teams.
Experience analyzing structured datasets to identify trends, validate outputs, and support product and business decisions.
Experience developing business cases, conducting ROI analysis, and measuring performance using KPIs.
Experience prioritizing product features and planning roadmaps based on business value, feasibility, and impact.
Experience designing and managing outputs across multiple dimensions, such as metrics, channel hierarchies, and business structures, for consistency and reconciliation.
Experience defining, monitoring, and analyzing forecast-to-actual performance metrics across segment, SBU, and department levels.
Experience supporting experimentation frameworks, including A/B testing and model performance evaluation.
Experience with data visualization and reporting tools such as Tableau or Power BI.
Experience documenting product requirements, analytical logic, workflows, and data definitions.

Responsibilities

Lead product development for enterprise financial forecasting platforms covering financial and operational business metrics across multiple channels.
Translate Finance, Merchandising, and Operations requirements into scalable product specifications and workflows.
Manage forecast outputs across metric, channel, department, and category hierarchies, ensuring consistency and reconciliation.
Partner with data science teams to define machine-learning model inputs, outputs, validation frameworks, and feedback loops.
Design and maintain channel-mapping logic to support accurate aggregation, disaggregation, and alignment of forecasts.
Collaborate with Finance leaders, Merchandising department heads, category planners, Data Science, and Engineering to align forecasting outputs with planning cycles and business processes.
Develop business cases and quantitative frameworks to evaluate forecast accuracy, financial impact, and return on investment.
Define and monitor KPIs and analyze forecast-to-actual variances across segment, SBU, and department levels.
Drive the transition from manual Excel-based forecasting and reporting to automated, governed forecasting systems.