Data Scientist

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

Role overview

A retail technology organization is hiring a Data Scientist for its Decisions & Insights team, which partners across client experience, strategy, marketing, merchandising, support, and engineering to translate complex data into actionable strategy. The role focuses on experimentation, causal inference, advanced analytics, and applied AI to understand not only what happened but why and what should happen next. The position owns ambiguous, high-impact analytical problems end-to-end, blending technical depth with business judgment to influence executive decisions.

Responsibilities

• Design and analyze experiments, observational studies, and causal inference models that explain client and business outcomes.
• Develop statistical models, semantic layers, entity models, and repeatable analytical workflows that connect fragmented data sources.
• Drive complex analytical projects from problem framing through execution, measurement, and executive-ready communication.
• Partner with cross-functional teams to define success metrics, map client journeys, and surface product and experience improvements.
• Mentor other data scientists and apply LLMs, AI agents, and emerging tools to accelerate analysis and raise technical standards.

Requirements

• Three or more years of experience in data science or a related analytical role, ideally in e-commerce, retail, or another data-rich environment.
• Strong foundation in experimentation, causal inference, statistical modeling, and product analytics, including defining success metrics.
• Experience working with complex, interconnected datasets and building scalable data structures; familiarity with graph databases, semantic layers, or entity modeling is a plus.
• Proficiency in Python or R and SQL, with comfort building production-oriented analytical solutions.
• Demonstrated ability to use LLMs and AI agents to accelerate problem-solving and day-to-day workflows.
• Independent problem solver who can structure ambiguity, own initiatives end-to-end, and communicate technical concepts to business and executive audiences.

Benefits and work setup

• Competitive salary with US base range of $150,000–$177,000, plus eligibility for an annual bonus and restricted stock unit grants.
• Comprehensive medical, dental, vision, and other inclusive health and wellness benefits.
• Culture emphasizing integrity, innovation, diverse perspectives, team collaboration, growth mindset, and a focus on equity and sustainability.