Data Scientist II

Data Scientist II

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 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.

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 Will 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’re Looking For

· 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

Helpful 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: Hybrid – Greater Philadelphia

· Reports to: IT – Data Engineering

· Travel: Less than 15%

· Salary Range: $100,000–$120,000

Why this role is different

You’ll build models that power live warehouses, moving freight, and real decisions—improving the system every single day.

• You will help modernize the analytical and decision‑making backbone of a company that moves food every day.
• You will shape durable, production‑grade data science systems that operate under real‑world constraints, not toy datasets or offline experiments.

The Kind of Problems You’ll Solve

· Translating complex logistics and operational workflows into models that drive real decisions

· Designing forecasting, optimization, and anomaly‑detection solutions that remain reliable under operational load

· Embedding models into production systems where latency, uptime, and data quality matter

· Building observability into models so performance, drift, and impact are measurable from day one

· Modernizing legacy analytics and heuristics without disrupting live operations

This role is for someone who prefers substance over hype. You are comfortable operating where models must work every day—not just in notebooks—and where imperfect data, tradeoffs, and constraints are part of the job. You bring strong analytical depth, practical engineering discipline, and an appreciation for environments where reliability, trust, and operational impact matter more than novelty.

Operational Context

This role is primarily technical and office-based, with occasional interaction in operational environments depending on system needs.

Benefits Include

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, Additional disability benefit, Basic Life Insurance, Accidental Death and Dismemberment Insurance, Voluntary Life Insurance, Voluntary Spouse Life Insurance, Voluntary Child Life Insurance, Loan Solution, Health Flexible Spending Account, Dependent Flexible Spending Account, Commuter accounts, 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.

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. Possess strong arithmetic and reading skills. 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.