Stord Labs serves as the experimental engine for defining how fulfillment will scale across the network, and this role brings rigorous testing and analytical discipline to that mission.
As a Test & Analytics Engineer, you will design experimental frameworks, execute structured tests in live operational environments, and develop analyses that directly inform which technologies, systems, and workflows are deployed into Stord’s production network. Working within a physical fulfillment environment with real orders, constraints, and variability, you will apply statistical and experimental rigor to operational decisions with direct business impact.
This role bridges advanced analytics and real-world operations, translating complex datasets and experimental outcomes into clear, decision-grade insights. Your work will directly influence fulfillment performance, automation adoption, and network design at scale.
If you are motivated by applying quantitative rigor to real operational systems—and seeing your analysis 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 all operational experiments conducted within the lab environment
Establish disciplined test governance to ensure experiments are structured, comparable, and decision-ready
Rapidly discontinue experiments that do not demonstrate measurable operational improvement to maintain agility and resource efficiency
Workflow Testing & Execution
Design, execute, and analyze multi-pass picking workflows versus traditional single-pass picking to evaluate productivity, travel distance, and throughput impacts
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 and inventory logic
Field Integration & Operational Collaboration
Work closely with warehouse associates performing day-to-day fulfillment activities to ensure experimental design aligns with operational reality
Incorporate field feedback into test design, execution refinement, and interpretation of results
Basic Qualifications
Bachelor’s degree in a highly quantitative field; Master’s degree preferred
2+ years of experience in advanced analytics, process engineering, testing strategy, or operations analytics within high-volume logistics or 3PL environments
Strong expertise in statistical analysis and A/B testing methodologies, with ability to derive statistically significant and scalable conclusions from operational data
Advanced SQL skills for querying and analyzing warehouse and fulfillment 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 or process mapping in warehouse or manufacturing environments
Experience working with digital twin or simulation models to evaluate slotting logic and warehouse workflows at scale
Bonus Points
Prior experience as a functional lead supporting WMS or WCS workflow configuration and optimization
Experience partnering with product and operations leadership to transition experimental learnings into live production pilots and scaled deployments
