Test & Analytics Engineer

Stord•Atlanta, GA

About The Position

Stord Labs is the experimental engine for defining how fulfillment will scale across Stord’s network. The Test & Analytics Engineer brings rigorous testing, analytical discipline, and technical validation to that mission. The role designs experimental frameworks, executes structured tests, and evaluates software and hardware systems in live operational environments. Analyses will inform which technologies, systems, equipment, and workflows are deployed into Stord’s production network. Working in a physical fulfillment environment with real equipment, operational constraints, and variability, the engineer applies statistical rigor and hands-on testing methods to evaluate system performance, identify opportunities for improvement, and translate experimental outcomes into actionable business decisions. The role bridges advanced analytics, systems testing, and real-world operations, with work that influences fulfillment performance, automation adoption, and network design at scale.

Requirements

Bachelor’s degree in Engineering, Computer Science, Data Science, Statistics, Operations Research, or another highly quantitative or technical discipline.
At least 2 years of experience in software testing, hardware testing, systems validation, test engineering, process engineering, or advanced operations analytics.
Hands-on experience testing software and hardware systems, including physical equipment, machinery, automation technologies, or integrated technical systems.
Experience developing and executing structured test plans, test cases, validation protocols, and performance evaluations.
Strong analytical capabilities, including statistical analysis, experimental design, and A/B testing methodologies, with the ability to derive statistically significant and scalable conclusions from operational data.
Advanced SQL skills for querying and analyzing operational, system, or performance data.
Proficiency with data visualization tools such as Tableau or Power BI.
Programming experience in Python or R for data manipulation, scripting, and statistical analysis.
Experience conducting time-and-motion studies, process mapping, root cause analysis, or performance testing in complex operational environments.
Ability to work hands-on in a physical operating environment, interact with equipment and technical systems, execute tests, and troubleshoot issues.

Nice To Haves

Master’s degree.
Industry experience in manufacturing and industrial automation, automotive engineering, supply chain, logistics and fulfillment, healthcare technology and medical device testing, robotics, material handling, or industrial equipment.
Experience with WMS, WCS, MES, PLCs, robotics, or other industrial control systems.
Prior experience as a functional lead supporting WMS or WCS workflow configuration and optimization.
Experience with digital twin or simulation models for evaluating equipment performance, slotting logic, and operational workflows at scale.
Familiarity with automated testing frameworks, hardware-in-the-loop testing, system integration testing, or performance testing.
Experience partnering with product, engineering, and operations leadership to transition experimental learnings into live production pilots and scaled deployments.

Responsibilities

Define hypotheses, success metrics, and measurement frameworks for operational and technical experiments.
Establish structured, repeatable, comparable, and decision-ready testing protocols and governance.
Develop methodologies to evaluate software functionality and hardware performance, reliability, and integration.
Discontinue experiments that do not demonstrate measurable operational or technical improvement.
Design, execute, and analyze structured tests across physical equipment, automation technologies, software applications, and integrated systems.
Develop test plans, test cases, and validation frameworks to evaluate system functionality, performance, reliability, and scalability.
Identify, troubleshoot, and document hardware and software issues; work cross-functionally to isolate root causes and recommend corrective actions.
Evaluate interactions among physical equipment, control systems, software applications, and operational workflows.
Establish repeatable processes to validate new technologies before production deployment.
Design and analyze multi-pass picking workflows versus traditional single-pass picking, evaluating productivity, travel distance, and throughput.
Conduct time-and-motion studies and operational testing to assess how equipment, technology, and workflow changes affect performance.
Partner with warehouse associates to ensure test conditions reflect real-world constraints and behaviors.
Evaluate and model inventory strategies, including multi-SKU binning, dynamic slotting based on order profiles, and predictive replenishment.
Assess co-mingled inventory strategies and their effects on storage density, inventory availability, fulfillment speed, and replenishment efficiency.
Translate experimental results into recommendations for warehouse configuration, inventory logic, and technology deployment.
Work with warehouse associates, engineering teams, and technical stakeholders to align experimental design with operational reality.
Incorporate field feedback into test design, execution, and interpretation.
Collaborate with hardware, software, automation, and operations teams to validate integrations and resolve performance issues.
Translate technical and analytical findings into recommendations for operational pilots and scaled deployments.