O pozici
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.
About the Staff Data Scientist Position
Stord is revolutionizing the logistics industry with our cloud-based supply chain platform. We empower brands to compete and grow by providing end-to-end logistics solutions coupled with our modern platform of tools covering Order Management (OMS), Warehouse Management (WMS), Consumer Experience (Pre/Post Purchase), Demand Plannin
Co budeš dělat
- Tackle the Hardest Problems
- Own the most complex, ambiguous, and high-stakes modeling problems at Stord end-to-end, from initial framing through production deployment
- Conduct deep exploratory data analysis to validate assumptions and surface non-obvious insights
- Build predictive models for supply chain optimization and consumer-facing applications, including delivery time estimation, demand forecasting, routing optimization, personalized product recommendations, and customer profile enrichment and segmentation
- Write production-quality code that integrates cleanly with existing services and can be maintained by others
- Drive the Technology Stack & Standards
- Play a leading role in defining Stord's data science and ML technology stack, tooling, and infrastructure choices
- Work alongside fellow data scientists and ML ops to establish standards and best practices for model development, deployment, monitoring, and retraining
- Contribute to both the data science and ML ops sides of the stack as needs arise
- Document technical decisions and patterns in ways the broader team can build on
- Partner Directly with Engineering
- Embed with engineering teams t
Koho hledáme
- Postgres and BigQuery experience
- Deep understanding of statistical analysis and machine learning fundamentals
- Proven experience deploying and operating models in production environments, including monitoring and retraining
- Hands-on experience with ML ops practices: model versioning, pipeline orchestration, drift detection, and experimentation frameworks
- Experience with cloud platforms (AWS, GCP, or Azure)
- Proficiency with Git/GitHub and collaborative development workflows
- Required Soft Skills
- Technical credibility - earns trust as the expert on hard problems through demonstrated depth, not just seniority
- Communication - carries technical opinions clearly into leadership conversations and can make complex tradeoffs legible
- Pragmatism - focuses on delivering working solutions and iterates; doesn't wait for perfect conditions
- Collaborative - works openly with data scientists, ML engineers, and software engineers toward shared outcomes
- Self-directed - identifies what needs to be done in ambiguous situations without waiting for detailed specs
