Staff Data Scientist

🕒 2 days ago

🇺🇸 United States – Remote

⏰ Full Time

🔴 Lead

📊 Data Scientist

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Stord

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2015

☁️ SaaS

🚗 Transport

🛍️ eCommerce

SaaS • Transport • eCommerce

Stord is a cloud supply-chain company that combines fulfillment network operations with integrated SaaS (OMS/WMS) to power omnichannel and DTC e-commerce brands. It provides warehousing, last-mile and transportation services, order routing, inventory management, and consumer-facing delivery tools to improve conversion, speed up fulfillment, and protect brand experience. Stord serves growing B2B and direct-to-consumer brands across food & beverage, beauty, apparel and other retail categories, offering a customizable fulfillment network and software platform to optimize costs and delivery performance.

📋 Description

• 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 • 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

🎯 Requirements

• 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

🏖️ Benefits

• Health insurance • Flexible work arrangements • Professional development opportunities