Staff Data Scientist

About this role

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.

Stord is looking for a Staff Data Scientist, a senior individual contributor to anchor data science efforts on the most difficult and highest-impact problems at Stord. You'll drive ML and MLOps technology strategy and embed with engineering teams to ship production models across our supply chain, fulfillment, and consumer-facing platforms.

This is a dual-scope Staff role: part Architect, you'll define the data science and ML ops standards, tooling, and infrastructure the whole organization builds on, and part embedded Solver, you'll personally own and ship the highest-complexity modeling problems end to end. There are no direct reports. Your impact comes from technical depth and cross-team influence, at a scope and level of trust equivalent to Stord's senior leadership track.

Stord's primary cloud and AI stack is Google Cloud Platform and Claude (Anthropic). You'll help shape how agentic AI gets built into the org's data and ML infrastructure, not just as a personal productivity tool, but as part of the standards and tooling you're already responsible for defining.

Key Responsibilities • Own complex modeling problems end-to-end, from framing through production deployment

• Conduct exploratory data analysis and build predictive models for supply chain, logistics, and consumer applications

• Define data science and MLOps standards, tooling, and infrastructure across the organization

• Embed with engineering teams to integrate models into production systems

• Lead technical strategy conversations with engineering and product leadership

• Help shape how agentic AI and AI-augmented workflows (governed semantic layers, agent-assisted model development, AI-augmented MLOps) are incorporated into Stord's data infrastructure

Required Qualifications

Technical Depth • Expert-level Python with production code experience

• Strong SQL/Spark (Postgres, BigQuery)

• Statistical analysis and machine learning fundamentals, including causal inference and recommendation systems

• Production model deployment, monitoring, and retraining experience

• MLOps practices: model versioning, pipeline orchestration, drift detection

• Google Cloud Platform (BigQuery, Vertex AI, GKE/Kubernetes, Cloud Run), Stord's primary cloud and data stack

• Experience with or strong interest in agentic AI tooling for data science and ML ops, Stord's AI platform is Claude, and you'll help shape how agentic workflows get built into the org's data infrastructure

• Git/GitHub and collaborative engineering workflows

Working Style • Technical credibility and deep expertise in at least one hard technical domain

• Clear communication of complex concepts to engineering and business leadership

• Pragmatism and solution-focused delivery

• Self-direction in ambiguous, individual-contributor-track situations, this role has no direct reports; impact comes from technical depth and cross-team influence

Preferred Qualifications • Logistics, supply chain, or e-commerce background

• Recommendation systems or customer profile modeling at scale

• Real-time model serving and high-availability ML systems

• Elixir, TypeScript, or functional programming experience

• Kubernetes, CI/CD, and DataOps tooling familiarity

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