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
- 5+ 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
- Ability to travel domestically 25% annually.
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
Note: This role is not eligible for visa sponsorship or employment-based immigration support.
