Data Scientist, Experiments & AI Insights

stitchfix; United States; Remote; USD 150,000 - 177,000; Full time

Benefits offered by this job

Health insurance

Annual bonus

RSU grants

Medical/dental/vision

Job summary

Stitch Fix is seeking a Data Scientist for its Decisions & Insights team to translate complex data into actionable strategy across marketing, merchandising, and engineering. You will lead experimentation, causal inference, and applied AI initiatives to explain what happened and what should happen next, influencing executive decisions.

The role requires 3+ years in data science, strong stats and analytics, production-ready Python/R/SQL skills, and the ability to work with large interconnected

Qualifications

• Three or more years of experience in data science or a related analytical role, ideally in ecommerce/retail.
• Strong foundation in experimentation, causal inference, statistical modeling, and product analytics.
• Experience with complex datasets and building scalable data structures; familiarity with graph databases or entity modeling is a plus.
• Proficiency in Python or R and SQL; ability to build production-oriented analytics.

Responsibilities

• Design and analyze experiments, observational studies, and causal inference models.
• Develop statistical models, semantic layers, and repeatable analytical workflows.
• Drive complex analytical projects from framing to execution and executive communication.
• Partner with cross-functional teams to define metrics and surface product improvements.
• Mentor other data scientists and apply LLMs and AI tools to accelerate analysis.

Skills

Experimentation

Causal inference

Statistical modeling

Product analytics

LLMs & AI agents

Python/R

SQL

Tools

Python

R

SQL

Graph databases

Job description

Stitch Fix is seeking a Data Scientist for its Decisions & Insights team to translate complex data into actionable strategy across marketing, merchandising, and engineering. You will lead experimentation, causal inference, and applied AI initiatives to explain what happened and what should happen next, influencing executive decisions.

The role requires 3+ years in data science, strong stats and analytics, production-ready Python/R/SQL skills, and the ability to work with large interconnected