[Remote] Staff Data Scientist
Note: The job is a remote job and is open to candidates in USA. Stord is The Consumer Experience Company, revolutionizing the logistics industry with their cloud-based supply chain platform. They are seeking a Staff Data Scientist to tackle complex modeling problems, drive the data science and ML technology stack, and collaborate with engineering teams to enhance their platform's capabilities.
Responsibilities
- 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
- 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
- Embed with engineering teams to integrate models into production systems and ship features
- Work with engineers to deploy models as microservices or API endpoints and own their performance over time
- Participate in sprint planning and agile ceremonies
- Review code and provide feedback on data-related implementations
- Lead technical conversations with engineering and product leadership on data science strategy and investment
- Translate complex modeling approaches and tradeoffs into clear, actionable recommendations for non-technical stakeholders
- Identify high-leverage opportunities for data science across the platform and bring them forward with supporting analysis
Skills
- 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
- 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
- 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
Company Overview
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