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AI & Machine Learning Intern

W

Worldwide Shipping & Logistics

Internship
Remote
Machine LearningNatural Language ProcessingPythonData Analysis

AI/ Data Science Intern


Location: Brookings, SD/ Lewes, DE USA (Remote)

Department: Operations, Product & Analytics

Employment Type: Internship (Unpaid)


About Worldwide Shipping & Logistics (WSL)

Worldwide Shipping & Logistics (WSL) is building an AI‑powered smart shipping platform for both small parcels and freight, combining advanced technology with real human expertise to help businesses ship smarter, faster, and more cost‑effectively.


WSL already operates an online shipping platform for small parcels and freight, and we are now expanding it with new AI shipping tools, customized logistics solutions, API integrations, and app development that connects directly to eCommerce platforms and websites.


We’re looking for a Data Science Intern who wants to apply data, analytics, and basic ML skills to real product features that impact shippers and eCommerce businesses.


Role Overview

The Data Science Intern will support WSL’s next generation of AI-driven logistics tools. You will work with real shipping, pricing, and operational data to:

  • Improve rate and service recommendations
  • Support AI tools for routing, transit time, and delivery risk
  • Contribute to data models and logic used in API and app integrations for eCommerce platforms


This is a hands-on role where your work can directly influence product features used by actual customers.


Key Responsibilities

1. Advanced Data Analysis & Operational Insights

  • Perform structured and exploratory data analysis on parcel and freight datasets to identify trends, anomalies, carrier performance patterns, and cost‑efficiency opportunities.
  • Apply statistical and quantitative methods to evaluate transit times, lane performance, delivery accuracy, and customer shipment behavior.
  • Support development of data-driven insights that improve WSL’s logistics operations and customer experience.


2. AI & Predictive Modeling Support

  • Assist in designing and evaluating foundational models for:
  • Rate Optimization (carrier/service recommendation engines)
  • Mode Selection (parcel vs LTL vs FTL determination)
  • Transit Time Prediction
  • Delivery Risk Scoring
  • Prepare datasets, engineer features, test prototype models, and validate outputs under the supervision of senior staff.
  • Contribute to the evolution of WSL’s AI-powered platform by recommending logical improvements based on data evidence.


3. Data Pipeline, Automation & Quality Management

  • Clean, validate, and normalize data from multiple systems (TMS, carrier APIs, operational spreadsheets, and internal tools).
  • Develop automated scripts or workflows to streamline repetitive data processing tasks.
  • Monitor data integrity and identify gaps or inconsistencies that affect reporting accuracy or model performance.


4. Dashboard, Visualization & Reporting Development

  • Build and maintain dashboards in Excel, Power BI, Tableau, or Looker Studio to support real-time operational visibility.
  • Create executive‑level reports that summarize shipping volume, carrier performance, delivery compliance, customer behavior, and cost trends.
  • Collaborate with leadership to ensure analytics outputs support strategic planning and product development.


5. API, Product & Integration Support (Data Focused)

  • Partner with the product team to define the data structures and logic required for WSL’s expanding API ecosystem.
  • Rates API
  • Labels & Booking API
  • Tracking API
  • Freight Quote API
  • Validate API data responses, test payload logic, and provide analytical support for eCommerce integrations (Shopify, WooCommerce, marketplace platforms).
  • Support technical documentation with data definitions, field requirements, and logic explanations.


6. Collaboration in Tool & Feature Development

  • Work cross‑functionally with Operations, Product, and Software teams to contribute to the creation of new AI-enabled logistics tools.
  • Assist in the data component of developing customized logistics tools for SMBs, enterprise shippers, and reseller partners.
  • Participate in testing and validating early-stage features related to WSL’s eCommerce app integrations and platform enhancements.


Updated Degree Requirements


We are only considering candidates pursuing or holding degrees in:

  • Data Science
  • Artificial Intelligence / Machine Learning
  • Software Engineering
  • Computer Science


(Students in highly related quantitative computing programs may be considered on a case-by-case basis.)


Optional but Preferred

  • Experience with data visualization tools (Power BI, Tableau, Looker Studio, etc.).

Interest in or basic understanding of:

  • Machine learning / predictive modeling
  • Logistics, shipping, or supply chain
  • APIs and how applications talk to each other
  • eCommerce platforms (e.g., Shopify, WooCommerce, marketplaces)
  • Any exposure to shipping, pricing, or marketplace data is a plus, but not required.


Career Development & Learning Benefits

  • Work directly with real operational and product data in a growing logistics tech company.
  • Learn how data science influences product decisions, APIs, and app integrations.
  • Gain experience supporting AI‑enabled tools used by actual customers (rates, routing, transit time, and logistics automation).
  • Build portfolio-ready dashboards, analyses, models, and data-driven product concepts.
  • Receive mentorship from leadership and cross‑functional collaboration with Operations, Product, and Technology teams.
  • For the right long-term contributor, there may be an opportunity to transition into a Developer/Engineer role with negotiable compensation, which could include the possibility of future equity participation in the company (subject to performance, role fit, and mutual agreement).


What We Offer

  • Hands-on learning in AI-driven logistics, data products, and eCommerce integrations.
  • Flexible scheduling to support school and academic commitments.
  • Opportunity to take ownership of high-impact data mini‑projects that tie directly to real business outcomes.
  • Potential for extended internship or future employment for strong performers.
  • Negotiable long-term growth path for exceptional candidates, including the potential to discuss equity-based incentives or share participation as the platform and technology team scale.