Director of Business Analytics

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Established in 2022, Real Cold was founded to address the unmet needs of the food cold chain sector. By combining high-growth strategic locations, state-of-the-art facilities, and exhaustive offerings that include traditional storage programs and diverse value-added services (including DTC), the company has positioned itself as a collaborative and integrated provider for food retailers, producers, and distributors. This mission is reinforced through its highly bespoke solutioning and customer-centric approach.

The Real Cold platform operates a national, omni-channel network, inclusive traditional storage offerings, as well as comprehensive direct-to-consumer program, which can reach the majority of U.S. consumers within 1- or 2-day ground service. For more information on Real Cold, please visit  .

Real Cold is seeking a Director of Business Analytics to build the analytical capabilities, data foundations, and next-generation systems that will shape how the company operates and makes decisions.

This is not a traditional reporting role. The Director of Business Analytics will work deeply across operational processes, source systems, enterprise data platforms, and business workflows to understand how data is created, transformed, and used. The role will identify gaps in data quality and process consistency, architect durable solutions, and translate complex operational information into clear, actionable guidance for leaders across the organization.

The ideal candidate combines the technical depth of a data architect, the curiosity of an analyst, the practicality of an operator, and the executive presence of a strategic advisor. This person must be comfortable moving between SQL queries, warehouse processes, dashboard design, AI strategy, customer conversations, and executive presentations.

• Trace data from its point of creation within warehouse and operational systems through ETL pipelines, data lakes, enterprise platforms, and reporting layers.
• Develop a detailed understanding of how operational processes generate data and where inconsistent practices create quality gaps, incomplete records, or unreliable metrics.
• Conduct deep analysis across warehouse operations, customer activity, labor, inventory, productivity, service performance, and financial outcomes.
• Design scalable data models, architectures, workflows, and governance practices that improve data reliability and usability.
• Partner with operations, technology, finance, customer teams, and functional leaders to redesign processes that strengthen data integrity at the source.
• Influence teams across the organization to adopt more consistent processes, definitions, and data practices.
• Establish clear business logic, metric definitions, and data lineage for critical enterprise KPIs.
• Identify root causes rather than simply reporting symptoms.
• Architect resilient systems that can support current analytical needs while preparing the organization for AI-enabled workflows, automated ingestion, and agentic applications.

• Design and deliver dashboards that help users understand what happened, why it happened, and what action should be taken.
• Move the organization beyond static reporting toward decision-support tools that surface risks, opportunities, exceptions, and recommended areas of focus.
• Build analytical products for general managers, operational leaders, executives, customers, and other stakeholders.
• Develop intuitive visualizations for critical KPIs such as labor productivity, inventory accuracy, throughput, occupancy, order performance, service quality, and customer profitability.
• Ensure dashboards are trusted, scalable, well-documented, and tied to clearly defined business processes.
• Evaluate dashboard adoption and continuously improve analytical products based on how users make decisions.

• Translate data into practical insights that help general managers and functional leaders improve operational and financial performance.
• Identify the key levers that drive productivity, service, labor efficiency, customer value, and profitability.
• Communicate complex findings in clear, concise, and understandable terms for both technical and nontechnical audiences.

• Help define and execute Real Cold’s long-term strategy for enterprise analytics, artificial intelligence, and intelligent automation.
• Design systems that are optimized for AI workflows, agentic ingestion, semantic retrieval, automated analysis, and decision support.
• Identify practical AI use cases across warehouse operations, customer service, forecasting, labor management, commercial…