Stord is The Consumer Experience Company, powering seamless checkout through delivery for today's leading brands. Stord is rapidly growing and is on track to double our revenue in the next 18 months. To meet and exceed this target, Stord is 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 AG1, True Classic, Native, Seed Health, quip, 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.
Turn Supply Chain Data Into Decisions
Most data roles at early-career level have you pulling reports someone else designed. This one doesn't.
At Stord, we're building the operating system for the modern supply chain, a unified platform handling Order Management, Warehouse Management, Transportation, and Consumer Experience for brands doing over $10B in commerce annually. The data behind that platform is massive, complex, and consequential. Shipments, inventory positions, order flows, warehouse
throughput, carrier performance it's all live, all connected, and all waiting to be understood better.
We're hiring new graduates into our data organization across three tracks: Analyst, Engineer, and Scientist. You'll apply for the role, tell us where your strengths are, and we'll place you on the track that fits. All three tracks work closely together the best data orgs do.
Where You'll Work
This role is based in our Atlanta office, located at our headquarters near Hartsfield-Jackson Airport in Union City, GA.We're in-person a minimum of 3 days per week.
Proximity to operations matters in a data role more than most. You'll be close to the warehouse floor, the ops team, and the product teams generating the data you work with. That context
makes your analysis sharper and your models more grounded.
The Three Tracks
Data Analyst: You turn data into decisions. You'll partner with product, operations, and leadership to answer hard questions about how the business is performing and why. Your work surfaces what's working, what isn't, and what to do about it.
● Build and maintain dashboards and reporting that teams actually use
● Write SQL to answer business questions quickly and accurately
● Dig into anomalies when a metric moves, you find out why
● Translate analytical findings into clear recommendations for non-technical stakeholders
● Define and track KPIs for product areas and operational workflows
● Partner with Data Engineers to make sure the data you need is clean, accessible, and trustworthy
Data Engineer: You build the infrastructure that makes everything else possible. You'll design and maintain the pipelines, models, and systems that move data from raw sources to reliable, queryable form across Stord's platform.
● Build and maintain data pipelines that ingest, transform, and deliver data at scale
● Develop and document dbt models that serve as the foundation for analytics and reporting
● Maintain data quality standards own the reliability of what's downstream of your pipelines
● Work with engineering teams to instrument new data sources as products are built
● Support Analysts and Scientists with the data infrastructure they need to do their best work
● Contribute to data platform tooling, orchestration, and observability
Data Scientist: You build models that make the platform smarter. You'll apply statistical and machine learning techniques to problems where the answers aren't in a dashboard — demand forecasting, anomaly detection, carrier optimization, and more.
● Develop and deploy predictive models that improve operational and product outcomes
● Work with Analysts to move from descriptive to predictive and prescriptive insights
● Design experiments and measure the impact of product and operational changes
● Translate complex modeling work into recommendations that non-technical teams can act on
● Partner with Data Engineers to operationalize models in production
● Stay current on applied ML techniques relevant to supply chain and logistics
What We're Looking For
Across all three tracks, we're looking for the same foundation:
● Strong SQL skills: you can write queries without an ORM doing the work, and you understand what's happening under the hood
● Comfort with Python: for analysis, scripting, or modeling depending on the track
● Analytical rigor: you ask the right questions before jumping to answers, and you know how to be wrong gracefully
● Clear communication: you can explain what the data says, what it doesn't say, and why the difference matters
● Ownership mindset: you follow your work through to impact, not just to delivery
● Comfort with AI tools: you use them to move faster without letting them think for you
Track-specific strengths we're looking for:
Analyst: Strong data visualization instincts, experience with BI tools (Looker, Tableau, Mode, or similar), comfort presenting findings to non-technical audiences
Engineer: Familiarity with data pipeline concepts, exposure to tools like dbt, Airflow, Spark, or cloud data warehouses (Snowflake, BigQuery, Redshift); software engineering fundamentals
Scientist: Coursework or project experience in statistics, machine learning, or applied modeling; comfort with scikit-learn, pandas, or similar; ability to frame a business problem as a modeling problem
What Success Looks Like:
30 days: You understand Stord's data landscape, know the key metrics your team tracks, and have contributed meaningfully to at least one live deliverable. You're asking good questions and not waiting to be pointed at work.
90 days: You're owning your own analyses, pipelines, or models with light oversight. The teams you support trust your output. You've surfaced at least one insight or data quality issue that changed how someone made a decision.
6 months: You're a reliable, independent contributor. You have opinions about how the data org should evolve and the credibility to back them up.
Why Stord
● Real data, real consequences: you're not working on synthetic datasets or internal dashboards nobody reads. The data you work with drives live operational decisions
● Cross-functional exposure:you'll work alongside product, engineering, operations, and leadership in a way that builds business intuition most data roles take years to develop
● AI-forward culture: we use AI tools as a genuine part of how we work, and we'll expect you to as well
● The right moment: Stord's data infrastructure is being built in real time. The decisions you make here will shape how the organization uses data for years