Data Scientist II

Camden
2 Aquarium Drive
Suite 400
Camden, NJ 08103, USA

US Cold owns and operates one of the most complex temperature‑controlled logistics networks in North America. Every day, our systems coordinate the storage and movement of food at national scale across a network of state‑of‑the‑art distribution centers, including multiple highly automated warehouse facilities.

We continue to advance our core warehouse and logistics platforms. Our current focus is on modular, event‑driven, API‑first and cloud architectures. We continue to enhance reliability and accelerate engineering productivity by strengthening our SRE and AI practices. This is a large investment in innovation to continue to drive operational excellence at our facilities.

If you want to build durable systems that operate in the physical world at scale, this is that opportunity.

We are hiring a Data Scientist to grow the capabilities of the organization to drive innovation, support data‑driven decision making, and transform both business and operational practices.

You will solve problems using statistical methods, machine learning, and AI.

You will help the organization frame and answer analytical questions grounded in data.

You will participate in research and development projects.

This role is ideal for a hands‑on, applied data scientist who enjoys working on complex systems, translating ambiguous business problems into analytical models, and seeing their work put into production.

• Identification, framing, and delivery of high‑impact analytical and optimization problems across operations, logistics, and the business
• Development, deployment, and lifecycle management of statistical, machine learning, forecasting, and optimization models used in operational decision‑making
• Large‑scale analysis of data from WMS, TMS, ERP, and operational systems to generate actionable insights
• Production‑grade analytical solutions built in Python and SQL, from prototype through operationalization partnering with business
• Model validation, performance monitoring, and continuous iteration based on real‑world outcomes
• Communication of insights, tradeoffs, and recommendations to both technical and non‑technical stakeholders
• Applied data science use cases including network and route optimization, warehouse optimization, demand and capacity forecasting, anomaly detection, and customer/product segmentation

• Multi‑facility, high‑availability Warehouse management and logistics systems
• Migration toward cloud‑native, event‑driven architectures
• Azure cloud‑native services
• Snowflake for real‑time data warehousing
• High‑availability and disaster‑recovery–first design
• AI mindset with application of optimization and predictive models for warehouse optimization, routing, consolidation, and capacity planning

• 3–5 years of experience in applied data science, machine learning, or advanced analytics roles
• Strong programming skills in Python; experience using SQL to work with large datasets
• Experience building, validating, and deploying analytical or machine learning models in production environments
• Solid foundation in statistics, optimization, or forecasting techniques
• Strong problem‑solving skills and comfort working with ambiguous, real‑world data
• Curiosity and willingness to learn the operational realities of cold storage and 3PL logistics
• Excellent communication skills, with the ability to explain technical concepts to non‑technical audiences
• Education:
  
  Master’s degree in mathematics, statistics, physics, computer science or related field

• Experience with Microsoft Azure, including data or ML‑related services
• Experience containerizing or deploying solutions using Docker
• Familiarity with optimization techniques, simulation, or decision‑support models
• Experience working with time‑series forecasting or network optimization problems
• Exposure to reinforcement learning or advanced optimization methods in applied settings
• Experience working in supply chain, logistics, manufacturing, or operations‑heavy environments

• Location:…