Lead Data Scientist

StordAtlanta, GA
Onsite

About The Position

Stord is seeking a highly skilled Lead Data Scientist to serve as the primary analytics and modeling expert within their core innovation team. This role is embedded directly in a live fulfillment environment, focusing on building digital twins, developing predictive and prescriptive models, and evaluating agentic AI systems against real-world warehouse workflows inside a dedicated micro-fulfillment facility. The work will directly inform how innovations scale across Stord’s broader fulfillment network, translating experimental results into enterprise-level operational strategies. The Lead Data Scientist will serve as the technical backbone of a five-person innovation team, partnering closely with controls engineers and operations specialists, and collaborating with frontier AI organizations and academic research partners.

Requirements

  • Master’s degree or PhD in Data Science, Operations Research, Computer Science, Industrial Engineering, or a highly quantitative field.
  • 5+ years of applied data science experience in supply chain, logistics, manufacturing, or other complex operational environments.
  • Advanced proficiency in Python, R, and SQL.
  • Proven experience building discrete-event simulations, continuous simulations, or digital twin systems using tools such as AnyLogic, Simio, FlexSim, or custom frameworks.
  • Strong track record of deploying machine learning and optimization models into live production or operational decision systems.

Nice To Haves

  • Experience operating as a standalone data scientist in an R&D lab, innovation center, startup environment, or advanced manufacturing technology setting.
  • Familiarity with WMS/OMS data structures and warehouse operational datasets.
  • Experience experimenting with large language models (LLMs) or agentic AI systems for workflow automation, exception management, or decision support in operations contexts.

Responsibilities

  • Lead the design and development of digital twin models that accurately replicate end-to-end warehouse operations.
  • Ingest and structure operational data from the micro-fulfillment lab to build scalable macro-simulations capable of representing enterprise-scale environments with tens of thousands of SKUs.
  • Stress test operational strategies—including slotting algorithms, multi-pass picking, batching logic, and automation workflows—within simulation environments prior to production deployment.
  • Design, test, and deploy AI-driven decision systems directly into operational workflows.
  • Develop models for forecasting, labor planning, inventory optimization, task prioritization, and exception handling to improve throughput, speed, and cost efficiency.
  • Build lightweight, production-ready analytical tools and algorithms that improve operational performance without heavy infrastructure overhead.
  • Translate operational data into financial impact models, linking time-and-motion studies to margin improvement, productivity gains, and labor efficiency.
  • Partner with operations analysts to design robust experimental frameworks, including success criteria, measurement methodologies, and statistical validation approaches.
  • Analyze complex, multi-variable experiments such as inventory commingling strategies and their impact on density, availability, and fulfillment speed.
  • Serve as the primary technical interface with external AI organizations, frontier model providers, and technology partners.
  • Collaborate with academic institutions to sponsor applied research in simulation, optimization, and AI-driven operations.
  • Integrate external research and capabilities into real-world operational testing within fulfillment workflows.

Benefits

  • Stord participates in E-verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S.
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