Lead Data Scientist, AI

Floor & DecorAtlanta, GA
21h

About The Position

Purpose: As a foundational member of our AI Center of Excellence, you will serve as the data science lead for enterprise AI initiatives, architecting and deploying AI solutions that make a meaningful impact across our national retail footprint. The Data Scientist Lead will work with other members of the AI COE and business leadership to identify and execute the highest-impact initiatives, own the data science lifecycle, from hypothesis and feature engineering to model validation and performance monitoring; bridging the gap between cutting-edge AI capabilities and practical business applications. This role requires a rare blend of deep technical mastery and sharp business acumen, to translate complex data into actionable insights and intelligent systems that enhance customer experience, optimize commercial operations, and enable smarter decision-making at scale. The ideal candidate is passionate about retail innovation, thrives in ambiguity, and is energized by the opportunity to shape AI strategy from the ground up. You’ll Be Successful With Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field. Master's degree preferred. 5+ years in Data Science or Applied AI roles, preferably in retail or a customer-facing industry. Proven track record of moving models from development into production which deliver measurable impact to the business. Expert proficiency in Python and SQL. Comfortable with version control. Expertise in supervised/unsupervised learning and modern frameworks (e.g. scikit-learn, PyTorch, or TensorFlow). Hands-on experience building with LLMs, RAG architectures, prompt engineering, or AI agent development. Experience deploying and monitoring models at scale. Familiar with cloud data platforms (e.g. Databricks or Snowflake) and cloud infrastructure (Azure experience a plus). You understand how to apply AI to commercial problems such as demand forecasting, customer- and associate- facing applications, personalization, labor optimization, etc. The ability to translate "black box" model outputs into clear, actionable insights for business leadership. Proven ability to communicate complex technical concepts to non-technical stakeholders and influence decision-making through data-driven storytelling. Strong intellectual curiosity with a bias toward action and continuous improvement. Demonstrated ability to work autonomously while collaborating effectively within cross-functional teams.

Requirements

  • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field. Master's degree preferred.
  • 5+ years in Data Science or Applied AI roles, preferably in retail or a customer-facing industry.
  • Proven track record of moving models from development into production which deliver measurable impact to the business.
  • Expert proficiency in Python and SQL. Comfortable with version control.
  • Expertise in supervised/unsupervised learning and modern frameworks (e.g. scikit-learn, PyTorch, or TensorFlow).
  • Hands-on experience building with LLMs, RAG architectures, prompt engineering, or AI agent development.
  • Experience deploying and monitoring models at scale.
  • Familiar with cloud data platforms (e.g. Databricks or Snowflake) and cloud infrastructure (Azure experience a plus).
  • You understand how to apply AI to commercial problems such as demand forecasting, customer- and associate- facing applications, personalization, labor optimization, etc.
  • The ability to translate "black box" model outputs into clear, actionable insights for business leadership.
  • Proven ability to communicate complex technical concepts to non-technical stakeholders and influence decision-making through data-driven storytelling.
  • Strong intellectual curiosity with a bias toward action and continuous improvement.
  • Demonstrated ability to work autonomously while collaborating effectively within cross-functional teams.

Responsibilities

  • Buy vs Build leadership. Evaluate 3rd-party AI platforms and partnerships. Serve as the technical lead in vetting vendor methodologies, guiding the in-house vs external decisioning.
  • Partner with business leadership to identify high-value AI opportunities, defining technical specifications and success metrics that align with enterprise strategy.
  • Design, develop, and deploy custom machine learning models (impacting merchandising, commercial, labor, digital, etc.) within the Databricks environment.
  • Lead experimentation design, including A/B testing and causal inference, to validate model performance and measure true incremental business lift (ROI).
  • Collaborate with data engineers on feature development and with AI developers to wrap models into production-grade APIs and applications.
  • Partner closely with the Customer Insights team to ensure model outputs are optimized for consumption within Power BI/DAX, turning complex predictions into actionable insights.
  • Establish and enforce MLOps standards across the org, including model versioning, automated retraining, and drift monitoring.
  • Serve as the primary ML subject matter expert for the broader Data Science & Insights team. Provide active coaching to analytics leaders, empowering them to identify ML-applicable use cases and effectively incorporate predictive outputs into their own functional workstreams.
  • Contribute to the enterprise AI governance framework, ensuring ethical AI practices, data privacy compliance, and model transparency.
  • Present findings, recommendations, and project updates to leadership and cross-functional partners in clear, compelling formats.
  • Be compliant with all appropriate privacy and security protocols.

Benefits

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