Director of Business Analytics

RealCold is a cold chain logistics company providing storage and value-added services through a national, omnichannel network. The Director of Business Analytics will build analytical capabilities, data foundations, dashboards, and next-generation analytics and AI systems while partnering across operations, technology, finance, and customer teams to improve decision-making and business performance.

Responsibilities:

• 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 RealCold’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 functions, and enterprise processes
• Evaluate and implement AI tools that improve the speed, quality, and accessibility of analysis
• Prototype emerging solutions and determine where experimentation can be converted into scalable business capabilities
• Serve as a strategic partner to senior executives, general managers, operational leaders, and customer-facing teams
• Build a comprehensive understanding of RealCold’s operational processes, technology ecosystem, data flows, and analytical needs
• Lead complex cross-functional initiatives involving data architecture, process improvement, analytics, and technology
• Establish standards for data quality, analytical design, metric consistency, and insight delivery
• Develop trusted relationships with stakeholders and use influence to drive process and behavioral change
• Represent RealCold externally in customer discussions involving analytics, data integration, reporting, and technology capabilities

Requirements:

• Bachelor's degree in data science, Computer Science, Mathematics, Statistics, Economics
• Minimum five (5) years of experience in business analytics, data architecture, data engineering, operational analytics, or a related field
• Significant experience with Warehouse Management Systems (WMS), with strong preference to Blue Yonder or Extensiv
• Advanced SQL skills, including the ability to investigate complex data structures, validate logic, identify anomalies, and develop scalable data models
• Experience with enterprise data platforms such as Snowflake, Databricks, or comparable technologies
• Strong knowledge of ETL processes, data orchestration, & data transformation
• Experience designing executive, operational, and customer-facing dashboards
• Demonstrated ability to identify business insights and translate analysis into operational or financial value
• Familiarity with modern AI tools, intelligent agents, and AI-ready data architecture
• Proven ability to lead through influence across technical, operational, and executive stakeholder groups
• Excellent written, verbal, and presentation skills
• Ability to synthesize technical and operational complexity into clear recommendations and compelling business narratives
• Experience in Python for data analysis, automation, integration, modeling, or application development
• Experience working with complex operational data, ideally within logistics, warehousing, supply chain, manufacturing, retail, or another process-intensive environment
• Able to stay focused on solutions that work in real operating environments
• Willing and able to personally investigate data, write queries, build prototypes, and work through detailed operational issues
• Energized by building capabilities in a growing organization where processes, platforms, and requirements continue to evolve
• Motivated to understand how the business truly works and unwilling to accept surface-level explanations
• Capable of driving process change across teams without relying solely on formal authority
• Able to connect individual analyses and technology decisions to broader enterprise objectives
• Confident and credible when interacting with senior leadership and external customers
• Must be able to pass a background check
• Ability to work well under pressure