About
Starting Semester: Fall 2026Assigned: No
Location: Remote/ Atlanta DC
DHL eCommerce
Client Profile
DHL eCommerce is one of four DHL business units, providing international and domestic e‑commerce delivery services across select markets in the Americas, Asia Pacific, and Europe. The division is focused exclusively on B2C online merchants, supporting the shipment of lightweight packages and parcels both domestically and internationally.Project Description
Ground network transformationDHL eCommerce currently relies on third‑party transportation providers and their fleets for all linehaul cargo movements across the U.S. network. This multi‑million‑dollar annual operation supports time‑critical parcel flows to and from 18 national distribution centers.
This project focuses on the design of a next‑generation, in‑house ground cargo management platform and operating model that could replace or supplement the existing outsourced solution. Teams will architect a fully integrated logistics technology stack—combining data engineering, transportation network optimization, automation, and operations analytics—to evaluate the financial, operational, and strategic feasibility of internalizing this function.
Project Scope
· Evaluate the cost feasibility of purchasing a fleet of 53’ trailers and hiring operating personnel
· Develop predictive ETA and in‑transit risk monitoring capabilities
· Model DC‑to‑DC pickup and delivery flows using network simulation techniques
· Design vendor management frameworks, SLAs, and compliance metrics
· Quantify expected cost savings versus the current third‑party model
Project Objectives (Technical & Strategic)
1. Advanced Cost & Network Optimization Analysis
· Build a SQL/Python‑based comparative cost model for in‑house versus outsourced operations
· Analyze primary cost drivers including linehaul, fleet acquisition, maintenance, operations, and penalties
· Apply network design and simulation tools to identify optimal routing and DC assignments
2. Workforce Modeling & Operational Architecture
· Determine required FTEs using workload, volume, and cycle‑time modeling
· Recommend staffing profiles with benchmarked productivity metrics
3. Implementation Blueprint
· Develop a phased implementation roadmap including systems, process migration, and KPI setup
· Propose future‑state data flows, automation opportunities, and architecture diagrams
Technical Environment & Communication Structure
· Weekly collaboration with the DHL project lead using real operational data
· Dedicated Microsoft Teams channel for file sharing, whiteboarding, and workflow tracking
· Cloud‑based Databricks environment supporting SQL, Python, ML, and simulation modeling
Deliverables
1. Current State System Audit
End‑to‑end mapping of the existing third‑party operating model, systems, integrations, and process gaps.
2. Cost Model & Workforce Requirements
· SQL/Python‑driven cost‑to‑serve model
· FTE forecasts with job architecture and labor cost impact
· Sensitivity analysis across volume, network, and SLA scenarios
3. Future‑State Ground Network Model & Operating Plan
· Recommended fleet size, network routes, and transportation flows
· Options for a full fleet, hybrid fleet, and comparisons of cost
· Predictive monitoring and automated exception management design
· System architecture including data pipelines, dashboards, and workflow automation
4. End‑to‑End Implementation Roadmap
· Timeline, deliverables, risk assessment, required technologies, and transition plan
· RACI matrix and KPIs for go‑live and stabilization phases
Skills
Required Skills & Capabilities· Value Stream Mapping & Lean Process Engineering
· Transportation Network & Linehaul Design
· Advanced Analytics (Databricks, SQL, PySpark, Python)
· Simulation Modeling (AnyLogic, SimPy, Python‑based tools)
· Predictive Analytics & ETA Modeling
· Cost‑to‑Serve & Financial Impact Analysis
· Systems Design & Control Tower Architecture
· Multi‑constraint logistics problem solving