Machine Learning Data Scientist - Logistics Algorithms

About the Role

Stitch Fix is seeking a Machine Learning Data Scientist - Logistics Algorithms to join our Logistics Algorithms team. This remote role is open to candidates across the United States. You will design, implement, and deploy ML-powered decision systems that optimize routing, delivery speed, and overall logistics efficiency for Stitch Fix customers.

What You'll Do

• Develop and deploying machine learning and optimization models for routing, capacity planning, demand forecasting, and other logistics challenges within Stitch Fix's supply chain network.
• Ingest, clean, and analyze large-scale logistics data; build features and experiments to improve model performance and business impact.
• Collaborate with software engineers, data platform teams, and product stakeholders to productionize models and monitor their performance in live systems.
• Design and run experiments, quantify impact, and communicate insights to cross-functional teams.
• Help build scalable analytics infrastructure and leverage cloud-based tools to support data-driven decisions in logistics.

What We’re Looking For

• BS/MS/PhD in Computer Science, Statistics, Operations Research, or a related field.
• 3+ years of hands-on machine learning and data science experience, with hands-on work in routing/optimization a strong plus.
• Proficiency in Python (Pandas, NumPy) and SQL; experience with ML frameworks such as scikit-learn and TensorFlow or PyTorch.
• Experience with optimization libraries (e.g., OR-Tools) and routing problems (vehicle routing, capacity planning).
• Strong problem-solving skills, excellent communication, and ability to collaborate across product, engineering, and business teams.

Nice to Have

• Experience with Spark, Airflow, or similar data workflow tools.
• Experience with cloud platforms (AWS, GCP).

Location & Benefits

This is a remote role based in the USA. Stitch Fix offers competitive benefits including health, dental, vision, 401(k), paid time off, and opportunities for professional growth.