Data Scientist

Build the intelligence that optimizes the movement of food at national scale Who We Are: 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. The Role: 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. What You’ll Own: 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 Technical Environment: Multi-facility, high-availability Warehouse management and logistics systems Migration toward cloud-native, event-driven architectures Azure cloud-native services CI/CD-driven delivery model 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 What We Are Looking For: 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 Preferred Experience: 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 Compensation & Structure: Location and Department: Greater Philadelphia (Hybrid), Information Technology Reports to: Senior Data Scientist Travel: Less than 15% Full-time, Exempt Salaried, Bi-Weekly Paid Salary Range: $105,000.00 - $130,000.00/yr. Operational Context: This role is primarily technical and office-based, with occasional interaction in operational environments depending on project and system needs. Benefits Include: If annual hours are attained, these benefits may apply. Medical, Dental, Vision, Prescription, Legal Insurance, Pet Discount, Critical Illness, Accident Insurance, Hospital Indemnity, Long Term Care + Permanent Life Insurance, Identity Theft Protection, Short Term Disability Insurance, Long Term Disability Insurance, Supplemental Disability Insurance, Basic Life Insurance, Accidental Death and Dismemberment Insurance, Supplemental Life Insurance, Supplemental Spouse Life Insurance, Child Life Insurance, Loan Solution, Health Flexible Spending Account, Dependent Flexible Spending Account, Telemedicine, Virtual Primary Care, Prescription Savings Plan, Prescription Specialty Copay Assistance Program, Weight Management Program, Chronic Condition Management, Care Navigator Program, 24/7 Nurse Line, Expert Medical Opinion, Precious Additions Maternity Program, Health Advocacy, Employee Assistance Program, Digital Cognitive Behavioral Therapy, Digital Physical Therapy, Behavioral and Mental Health Platforms, Auto and home discount program, Secure Travel Protection, Discount Programs, 401(k) plan, Education Assistance, Paid Time Off, Referral program & Commuter Benefit (NJ ONLY). Physical & Operational Context: May require physical effort associated with using the computer to access information, or occasional standing, walking, lifting needed to carry out everyday activities. Effective communication, vision, and hearing are essential for safety and productivity. Operate scanners, tablets, radios, phones, computers, and other essential equipment as required. Additional work hours may be requested by management to help manage employee production, projects, and/or special events. Engage in frequent personal interaction and communication. Attend in-person meetings and/or training on a regular basis. Follow verbal instructions, written instructions, and company policies. Work independently and coordinate with others. Fast-paced environment, managing stress, and meeting productivity standards. Additional Information: Job functions may vary based on the area of operation. This description outlines the most common tasks required for the job. Reasonable accommodation may be provided to enable individuals with disabilities to perform essential duties. This job description may not encompass all tasks necessary to complete the role.