Pro90 ProblemsSQL + Python

Logistics SQL & Python Interview Questions

Shipping and delivery companies track parcel journeys, driver performance, and network efficiency across complex supply chains. These SQL and Python challenges are modeled after data work at Amazon Logistics, FedEx, UPS, DHL, XPO Logistics, Maersk, Flexport, CH Robinson, Uber Freight, ShipBob, and more. Build skills in on-time delivery analysis, route optimization, cost-per-shipment metrics, carrier performance, and warehouse efficiency.

Logistics

90 total problems

SQL45

Python45

Practice SQL Practice Python

Companies working in Logistics

These practice problems are modeled after the kind of data and analytics challenges teams in this industry typically face.

Amazon Logistics

UPS

FedEx

DHL

CH Robinson

XPO Logistics

Maersk

Flexport

Coyote Logistics

JB Hunt

Lineage Logistics

GEODIS

Kuehne+Nagel

DSV

Convoy

Uber Freight

GXO Logistics

ShipBob

Project44

FourKites

Company names and logos are trademarks of their respective owners, used here only to describe the kind of data these companies work with. Let's Data Science is not affiliated with, endorsed by, or sponsored by any company shown. Practice problems are original works and are not real interview questions from these companies. Rights & takedowns.

Difficulty Breakdown

90 problems

16 Easy(18%)

31 Medium(34%)

38 Hard(42%)

5 Expert(6%)

What You'll Practice

On-time delivery analysisRoute efficiency metricsNetwork capacity planningCost per shipmentDriver performanceCarrier comparisonSLA compliance trackingLast-mile analytics

Topics Covered

21 topics

SQL · 9

aggregationbasic queries filteringcleaning transformdate timejoinsscenario sqlset operationssubqueries cteswindow functions

Python · 12

eda statisticsfeature engineeringpandas aggregationpandas applypandas basicspandas cleaningpandas datetimepandas filteringpandas mergingpandas reshapingpandas scenariopandas window

All Problems90 total

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