ABOUT STORD
Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. Stord is rapidly growing and strategically scaling teams across the entire company, and seeking energetic experts to help us achieve our mission.
By combining comprehensive commerce-enablement technology with high-volume fulfillment services, Stord provides brands a platform to compete with retail giants. Stord manages over $10 billion of commerce annually through its fulfillment, warehousing, transportation, and operator-built software suite including OMS, Pre- and Post-Purchase, and WMS platforms. Stord is leveling the playing field for all brands to deliver the best consumer experience at scale.
With Stord, brands can increase cart conversion, improve unit economics, and drive sustained customer loyalty. Stord’s end-to-end commerce solutions combine best-in-class omnichannel fulfillment and shipping with leading technology to ensure fast shipping, reliable delivery promises, easy access to more channels, and improved margins on every order.
Hundreds of leading DTC and B2B companies like True Classic, Native, Seed Health, goodr, Sundays for Dogs, and more trust Stord to deliver industry-leading consumer experiences on every order. Stord is headquartered in Atlanta with facilities across the United States, Canada, and Europe. Stord is backed by top-tier investors including Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures.
Stord Labs serves as the experimental engine for defining how fulfillment will scale across the network, and this role brings rigorous testing, analytical discipline, and technical validation to that mission.
As a Test & Analytics Engineer, you will design experimental frameworks, execute structured tests, and evaluate both software and hardware systems in live operational environments. You'll develop analyses that directly inform which technologies, systems, equipment, and workflows are deployed into Stord's production network.
Working within a physical fulfillment environment with real equipment, operational constraints, and variability, you'll apply statistical rigor and hands-on testing methodologies to evaluate system performance, identify opportunities for improvement, and translate experimental outcomes into actionable business decisions.
This role bridges advanced analytics, systems testing, and real-world operations. We're particularly interested in candidates who have worked with complex machinery, automation, integrated hardware/software systems, or technical equipment in environments such as manufacturing, automotive, supply chain, healthcare, or logistics.
Your work will directly influence fulfillment performance, automation adoption, and network design at scale.
If you're motivated by applying technical and quantitative rigor to real-world systems and seeing your work directly shape how physical goods move through a large-scale logistics network, this role offers a rare opportunity to operate at that intersection.
What You'll Do:
Experiment Design & Governance
- Define clear hypotheses, success metrics, and measurement frameworks for operational and technical experiments conducted within the lab environment.
- Establish disciplined testing protocols and governance to ensure experiments are structured, repeatable, comparable, and decision-ready.
- Develop testing methodologies to evaluate both software functionality and hardware performance, reliability, and integration.
- Rapidly discontinue experiments that do not demonstrate measurable operational or technical improvement to maintain agility and resource efficiency.
Software & Hardware Testing
- Design, execute, and analyze structured testing 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/software issues, working cross-functionally to isolate root causes and recommend corrective actions.
- Evaluate interactions between physical equipment, control systems, software applications, and operational workflows.
- Establish repeatable testing processes to validate new technologies before transitioning them into production environments.
Workflow Testing & Execution
- Design, execute, and analyze multi-pass picking workflows versus traditional single-pass picking to evaluate productivity, travel distance, and throughput impacts.
- Conduct time-and-motion studies and operational testing to understand how equipment, technology, and workflow changes impact performance.
- Partner directly with warehouse associates executing fulfillment operations to ensure test conditions accurately reflect real-world constraints and behaviors.
Inventory Strategy & Analytics
- Evaluate and model advanced inventory strategies, including multi-SKU binning, dynamic slotting based on order profiles, and predictive replenishment systems.
- Assess co-mingled inventory strategies, measuring impact across storage density, inventory availability, fulfillment speed, and replenishment efficiency.
- Translate experimental results into actionable recommendations for warehouse configuration, inventory logic, and technology deployment.
Field Integration & Operational Collaboration
- Work closely with warehouse associates, engineering teams, and technical stakeholders to ensure experimental design aligns with operational reality.
- Incorporate field feedback into test design, execution refinement, and interpretation of results.
- Collaborate with hardware, software, automation, and operations teams to validate system integrations and resolve performance issues.
- Translate technical findings and analytical outcomes into clear recommendations for operational pilots and scaled deployments.
Basic Qualifications:
- Bachelor's degree in Engineering, Computer Science, Data Science, Statistics, Operations Research, or another highly quantitative or technical discipline; Master's degree preferred.
- 2+ years of experience in software testing, hardware testing, systems validation, test engineering, process engineering, or advanced operations analytics.
- Hands-on experience testing both 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 in 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, interacting with equipment and technical systems to execute tests and troubleshoot issues.
Relevant industry experience may include:
- Manufacturing and industrial automation
- Automotive and automotive engineering
- Supply chain, logistics, and fulfillment
- Healthcare technology and medical device testing
- Robotics, material handling, and industrial equipment
Bonus Points:
- Experience working 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 working with digital twin or simulation models to evaluate equipment performance, slotting logic, and operational workflows at scale.
- Familiarity with automated testing frameworks, hardware-in-the-loop (HIL) 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.
