Senior Data Analyst, Labor Operations

About the Role

This role sits in Stord's Data team and owns the analytics product layer for our Labor Management System (LMS). You're not inheriting a legacy setup—you're building alongside the team actively developing the LMS as a product. The Operations org is your customer, and your job is to understand what building GMs and area managers need from their data, delivering solutions without requiring hand-holding through requirements.

The need this role fills is specific: operational fluency combined with technical execution. You must walk into a conversation with a building GM, understand their decision-making and blockers, and return with a data product that solves their problem—not a list of clarifying questions. The operations team should never have to prescribe the solution. If you've been the trusted data team member who independently understands business problems, this is that role.

The analytical challenge is real: understanding what drives OPH (Orders Per Hour) changes across a multi-brand, multi-site network requires decomposing volume effects, brand mix shifts, order complexity, and genuine productivity signals. Designing this framework, making it legible to a building GM at 6am, and building it in partnership with the LMS product team—that's the job.

Responsibilities

• LMS Data Product Ownership
  • Own the end-to-end analytics layer for Stord's Labor Management System: requirements, build, maintenance, and quality.
  • Act as the primary interface between the Data team and the Operations org for all LMS analytics, translating operational needs into data product decisions without requiring the business to prescribe solutions.
  • Own the reliability of LMS data feeds into the analytics platform; be the first point of contact when a building GM reports data discrepancies.
  • Work closely with the LMS product manager and engineering team as a core partner, ensuring data observability requirements are integrated during feature scoping—not retrofitted.
  • Diagnose data quality issues, distinguishing between analytics pipeline problems and source system issues, and drive resolutions with LMS engineering.
  • Partner with data engineering to ensure upstream data pipelines support the accuracy and timeliness required for operational dashboards.
• Operator-Facing Dashboards (In-Shift, Live)
  • Build floor TV dashboards for area managers: real-time OPH, order pace vs. plan, labor utilization, and exception flags.
  • Develop shift-level summary views for supervisors and building GMs with a refresh cadence appropriate for in-shift decision-making.
• Analytics Layer for Operations Leadership
  • Build and maintain the reporting layer enabling the Operations team to conduct weekly performance analysis, including weekly OPH summaries, site comparisons, and trend views.
  • Design and own the decomposition framework that separates genuine productivity gains from brand mix shifts, volume changes, and order complexity effects, empowering the Operations team to answer "why did OPH change?" independently.
  • Ensure data and tooling are reliable and consistent, so the Operations analytics team is not blocked or dependent on you to interpret results.
• Methodology and Metric Ownership
  • Define and calculate OPH, UPH (Units Per Hour), UPO (Units Per Order), labor utilization, and related KPIs.
  • Design and maintain the analytical framework attributing OPH changes to root causes.
  • Document definitions and methodology to ensure clarity across the broader team.
• Data Quality and Integrity
  • Serve as the first line of defense for LMS data issues, including system migrations, source reconciliation, and anomaly detection.
  • Flag, document, and recommend handling for data irregularities (e.g., hours charged with no shipments).
  • Partner with data engineering to ensure LMS and WMS data flows are reliable and well-understood.

Requirements

• Track record of working as the interface between a data/analytics team and an operational business unit; trusted to understand business problems independently.
• Ability to sit with a building GM for 30 minutes, understand their decision drivers, and return with a dashboard spec without managerial intervention.
• 3-6 years of experience in operations analytics with direct exposure to fulfillment center, 3PL, or warehouse operations.
• Fulfillment center or 3PL building experience is critical.
• Industrial engineering, operations research, or quantitative supply chain background is a strong plus, particularly with hands-on analytics work.
• Strong SQL skills; comfortable querying raw operational data from an LMS, WMS, or equivalent without relying on pre-built datasets.
• Visualization proficiency in Tableau, Power BI, or equivalent; capable of building production-quality dashboards from scratch.
• Analytical methodology depth: experience designing decomposition analyses, attribution frameworks, or waterfall analyses; understanding of mix effects vs. rate effects.
• Operational fluency: hands-on experience with OPH, UPH, UPO, and labor utilization, not just theoretical knowledge.
• Bias toward rapid delivery: prototype quickly and iterate, rather than seeking perfection before sharing work.
• AI-first mentality: Stord is an AI-first company, and the team uses AI for coding, analysis, and summarizing/presenting results.

Preferred Qualifications

• Background in fulfillment operations analytics at a major 3PL or large-format retailer.
• Python for analysis (pandas, numpy, data wrangling).
• Familiarity with Labor Management Systems: Manhattan Active WM, Infor WFM, Kronos/UKG, Blue Yonder, or similar.
• Analytics engineering exposure (dbt, lightweight transforms, building reusable data models).
• Multi-site fulfillment network context: experience comparing building-level performance and explaining variance across sites to senior leadership.

About Stord

Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. We combine comprehensive commerce-enablement technology with high-volume fulfillment services to provide 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.

We are leveling the playing field for all brands to deliver the best consumer experience at scale. Hundreds of leading DTC and B2B companies—like AG1, True Classic, Native, Seed Health, quip, goodr, and Sundays for Dogs—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. We are backed by top-tier investors, including Kleiner Perkins, Franklin Templeton, Founders Fund, Strike Capital, Baillie Gifford, and Salesforce Ventures.

Our fulfillment buildings process tens of thousands of orders daily across an ever-expanding network. The data generated—labor performance, efficiency trends, brand-level throughput—is central to how we run the business and retain/grow brand relationships. Analytics is a competitive advantage, and we're investing in the people who can unlock it.