Senior Data Scientist, Digital

Floor & Decor Outlets of America, Inc. is hiring a Senior Data Scientist, Digital to build and run machine learning that improves the digital shopping experience.

Responsibilities

• Build and improve ML models for product search and discovery using proprietary signals including customer behavior, store-level availability, and local demand.
• Develop personalization and recommendation models for site and app, including “complete the project” recommendations and session-based models for anonymous and infrequent shoppers.
• Apply LLMs and computer vision to enrich product attributes at catalog scale, with quality controls aligned to technical product specifications.
• Partner with the Lead Data Scientist, AI/ML on conversational shopping and AI-assisted project guidance, owning retrieval quality and evaluation.
• Monitor and manage quality, cost, latency, and safety for AI-assisted experiences.
• Create durable ML assets that persist across eCommerce platform and vendor changes, including enriched product data, embeddings, and evaluation sets.
• Lead quantitative evaluation of search and personalization vendors using Floor & Decor’s own data, recommending when platform configuration is sufficient versus when proprietary models provide defensible value.
• Own production models on Databricks, provide documented outputs for Ecommerce and IT Engineering integration into site, app, and vendor platforms, and manage retraining and troubleshooting.
• Help expand ML capabilities on Databricks as needs grow, and with the Lead Data Scientist, AI/ML define scalable ML engineering standards for a growing team.
• Partner with Data Engineering, Product, and Engineering to define data and event tracking needed for training and measurement.
• Design and analyze A/B tests for model-driven features; measure incremental impact on conversion, average order value, and engagement.
• Ensure offline model improvements translate into online results; Ecommerce Analytics owns standard digital performance reporting.
• Support the digital data science roadmap by sizing opportunities, assessing feasibility, and clarifying what models will and will not do.
• Serve as technical lead for digital ML: guide work of the Data Scientist, Digital, raise technical quality via design and code reviews, and support recruiting and hiring.
• Maintain clear documentation of methodologies, model assumptions, and limitations to support reproducibility and continuity.
• Stay current on search, recommender systems, and applied generative AI and integrate relevant improvements into practice.
• Follow Privacy Preferences, Responsible AI, and Security protocols, including guardrails for customer-facing generative AI.

Requirements

• Bachelor’s degree in a related quantitative field (Computer Science, Statistics, Mathematics, Engineering, Economics, or similar). Master’s or PhD is a plus; relevant experience may substitute for education based on one calendar year of experience for one academic year of education.
• 5+ years of experience in data science or machine learning, or an equivalent combination of education and experience as determined by the company.
• Experience building ML for live, customer-facing digital products such as search, recommendations, ranking, personalization, or ads in eCommerce, marketplaces, media, or comparable environments.
• Proven ability to take multiple models into production and own them post-launch, including monitoring, troubleshooting, and retraining.
• Depth in search and ranking or in recommendations and personalization, with enough breadth to contribute across both.
• Applied experience with NLP, embeddings, and large language models, including retrieval and reranking and evaluating output quality.
• Expert proficiency in Python and SQL, with production-quality coding practices.
• Hands-on ML lifecycle experience with tooling such as automated training and scoring pipelines, deployment, and monitoring.
• Rigor in model evaluation and online experimentation using A/B testing for digital products.
• Comfort using AI-assisted development tools such as Claude Code, GitHub Copilot, or Cursor.
• Ability to work as the roadmap and platforms evolve: define ambiguous problems, start simple, and add complexity when it delivers value.
• Strong communication skills to explain model behavior, tradeoffs, and expected impact to product, engineering, and business leaders.

Technologies

• Python, SQL, Natural language processing, Embeddings
• Large language models, Retrieval, Reranking
• A/B testing, Claude Code, GitHub Copilot, Cursor
• Databricks, Azure, PySpark
• CI/CD, MLflow, Model registry, Model serving
• Feature stores
• Bloomreach, Constructor, Algolia, Dynamic Yield, Salesforce Personalization, Salesforce Commerce Cloud
• Retrieval-augmented generation (RAG), LLM-based agents

Benefits

• Bonus opportunities & career advancement opportunities at every level
• 401k with company match
• Employee Stock Purchase Plan
• Referral Bonus Program
• Medical, Dental, Vision, Life, and other Insurance Plans (subject to eligibility criteria)
• Paid vacation and sick time for eligible associates
• Paid holidays plus a personal holiday
• Paid Volunteer Time Off that starts on Day 1

Preferred Qualifications

• Experience helping establish an emerging ML function, including practices, tooling, and production patterns for a growing team.
• Databricks on Azure, PySpark, and CI/CD for ML, including MLflow, model registry, model serving, and feature stores.
• Experience extending, evaluating, or migrating commercial search/personalization platforms such as Bloomreach, Constructor, Algolia, Dynamic Yield, Salesforce Personalization, or Salesforce Commerce Cloud.
• Semantic search, RAG, or computer vision applied to product discovery.
• eCommerce or omnichannel retail experience, ideally in high-consideration, project-based categories (home improvement, furniture, home décor).
• Experience with LLM-based agents or tool-using workflows.
• Experience with clickstream and customer behavioral data at scale.
• Experience with causal inference methods for measuring impact.
• Experience mentoring other data scientists or serving as technical lead on a multi-person ML effort.

Working Conditions (Travel & Environment)

• Travel may be required, including air and car travel (typically less than 10%).
• Noise level in the work environment is typically quiet to moderate.

Location: Atlanta, GA (onsite)