Data Scientist

United State Cold Storage Inc / USCS•Camden, NJ

4d•$105,000 - $130,000•Hybrid

About The Position

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 on a 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 architecture. 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.

Requirements

Master’s degree in mathematics, statistics, physics, computer science or related field
2-4 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

Nice To Haves

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

Responsibilities

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