Jobs at EASE LOGISTICS SERVICES LLC

Perform accounts receivable tasks including collections, payments posting and reconciliation, invoice processing, customer inquiries, aging statements, cash projection, and month/end accounting support. Support process improvements and coach entry-level AR staff while ensuring compliance with accounting policies.

The Enterprise Sales Representative will generate leads, qualify prospects, and maintain relationships with Mid Market and Enterprise customers, focusing on growth and alignment with EASE’s services.

Design, build, and maintain Power BI dashboards and semantic models using DAX and RLS. Write complex T-SQL against Azure SQL, analyze and tune reports, ensure data quality with data engineers, translate business needs into measurable analytics, and support stakeholders across operations, finance, and sales. Contribute to analytics process improvements, governance, and team workflows.

Oversee daily warehouse operations and staff to ensure inventory accuracy, timely receiving and shipping, safety and GMP compliance, and productivity. Manage staffing, training, cycle counts, WMS/ERP and Excel-based reporting, process improvements, equipment operation, maintenance coordination, and driver/dispatch communication.

Drive new business and manage customer relationships for EASE Logistics through prospecting, onsite meetings, CRM tracking, and cross-functional coordination. Support billing/AR issues, meet sales quotas, attend events, and provide market feedback to operations.

The Account Manager builds relationships with key accounts, analyzes KPI metrics, organizes business reviews, identifies opportunities, collaborates with departments, and oversees operations ensuring client satisfaction and compliance through effective communication and leadership.

The Director of Product Development will lead product vision, AI strategy, manage teams, and ensure the development of an AI-enabled logistics platform. Responsibilities include building partnerships, managing product budgets, overseeing data science efforts, and establishing KPIs for performance and development.