Supply Chain & Data Analytics Intern

KitchenCrest Cabinets, LLC; Melrose Park (IL); On-site; USD 20,664 - 27,552; Part time

Benefits offered by this job

Hands-on experience in warehouse operations

Exposure to real-world applications of data analysis

Mentorship and collaboration with leadership

Job summary

KitchenCrest Cabinets, LLC is looking for a motivated Supply Chain & Data Analytics Intern in Melrose Park, Illinois. The role involves supporting warehouse operations, procurement strategies, and data-driven supply chain initiatives, ideal for students in sociology, statistics, or related fields.

This position offers hands-on experience in real-world applications of data and logistics, along with mentorship from leadership in a growing company.

Qualifications

• Currently pursuing a degree in Sociology, Statistics, Data Science, Economics, or a related field.
• Strong analytical and problem-solving skills.
• Interest in operations, supply chain, or logistics.
• Comfortable working with data; Excel required.

Responsibilities

• Conduct physical inventory counts and cycle counts across warehouse locations.
• Assist with tracking inbound shipments and purchase orders.
• Support development of a structured procurement network.
• Work with datasets to analyze trends and seasonality.

Skills

Analytical skills

Problem-solving skills

Communication skills

Organizational skills

Education

Degree in Sociology, Statistics, Data Science, or related field

Tools

Excel

Python

R

Job description

About KitchenCrest Cabinets (KCC):

KitchenCrest Cabinets (KCC) is a fast-growing cabinetry wholesaler specializing in Ready-to-Assemble (RTA) and assembled cabinet programs. With multiple distribution centers across the U.S., KCC is focused on scaling operations through data-driven decision-making, efficient logistics, and innovative supply chain strategies.

Position Overview:

KCC is seeking a highly motivated Supply Chain & Data Analytics Intern to support warehouse operations, procurement strategy, and data-driven supply chain initiatives. This role blends hands‑on operational work with analytical and strategic projects, making it ideal for students interested in sociology, statistics, and real-world applications of data in business operations.

Warehouse Operations & Inventory Management

• Conduct physical inventory counts and cycle counts across warehouse locations
• Audit inventory accuracy and identify discrepancies
• Support improvements in inventory tracking and warehouse processes
• Collaborate with warehouse teams to understand operational workflows

Supply Chain & Logistics Support

• Assist with tracking inbound shipments, purchase orders, and transfers between warehouses
• Analyze logistics data (lead times, fulfillment rates, stockouts)
• Support coordination between procurement, warehouse, and sales teams
• Help identify inefficiencies and propose process improvements

Procurement & Data Analytics Projects

• Support development of a structured procurement network across SKUs and locations
• Assist in building inventory forecasting models and demand planning frameworks
• Help design and test ordering cadences based on historical sales and variability
• Work with datasets to analyze trends, seasonality, and purchasing patterns
• Contribute to early-stage machine learning and predictive modeling initiatives for demand forecasting

What You’ll Gain:

• Hands‑on experience in warehouse operations and supply chain logistics
• Exposure to real-world applications of statistics and data analysis
• Experience working with inventory, procurement, and forecasting models
• Opportunity to contribute to high‑impact projects in a growing company
• Mentorship and direct collaboration with leadership

Qualifications:

• Currently pursuing a degree in Sociology, Statistics, Data Science, Economics, or a related field
• Strong analytical and problem‑solving skills
• Interest in operations, supply chain, or logistics
• Comfortable working with data (Excel required; Python/R is a plus but not required)
• Detail‑oriented and willing to work both in‑office and in a warehouse environment
• Strong communication and organizational skills

Preferred (Not Required):

• Experience with Excel (pivot tables, basic analysis)
• Exposure to data analysis tools (Python, R, SQL)
• Interest in machine learning or forecasting