Staff Data Scientist

Role Description

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 Planning, and more. As we continue to enhance our platform and look to the future, we are doubling down on our investment in Data and ML to make our platform even more powerful for the brands that use it.

We are seeking a Staff Data Scientist to serve as a technical anchor across our data science efforts. This is a senior individual contributor role where you will:

• Work on the most difficult and highest-impact problems at Stord.
• Drive the direction of our data science and ML technology stack.
• Help set standards and best practices alongside fellow data scientists and ML engineers.
• Work directly with engineering teams embedded in product development.
• Engage with leadership to shape how we invest in and apply data science across the platform.

In this role, you will be expected to move fluidly across data science and ML ops depending on where you're needed most. You'll work on areas such as:

• Demand forecasting
• Delivery date estimation
• Pricing analytics
• Network simulation
• Customer recommendations
• Customer profile management

This is a role for someone who thrives on hard problems, brings strong technical opinions, and can carry those opinions credibly into conversations with both engineers and executives.

Qualifications

• Expert-level Python programming with production code experience
• Strong SQL skills with 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

Requirements

• 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

Preferred Qualifications

• Background in logistics, supply chain, or e-commerce domains
• Experience building recommendation systems or customer profile modeling at scale
• Experience with real-time model serving and high-availability ML systems
• Experience with Elixir, TypeScript, or functional programming paradigms
• Familiarity with Kubernetes, CI/CD, and DataOps tooling
• Experience helping define standards or tooling choices across a data science team