Data Scientist, Loyalty

Floor & Decor; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Bonus opportunities

401k with discretionary company match

Employee Stock Purchase Plan

Relocation opportunities

Medical, Dental, Vision Insurance

Job summary

Floor & Decor seeks a data scientist to build and maintain models that support the PRO loyalty program, analyzing member behavior, reward dynamics, and customer lifetime value across the program lifecycle.

You will work cross-functionally with Loyalty/CX, PRO, Marketing/CRM, FP&A, and IT to drive data-driven decisions across the customer journey and optimize program outcomes.

Qualifications

• Bachelor’s degree in statistics, data science, CS, math, or economics; master’s preferred.
• 3+ years of data science/advanced analytics experience.
• Strong proficiency in SQL.
• Experience with Python and/or R.
• Experience with AI-assisted analysis tools (Claude, Codex).
• Loyalty or CRM analytics experience preferred.
• Excellent communication and cross-functional collaboration.

Responsibilities

• Model member behavior across program lifecycle and health.
• Quantify reward redemption and breakage by cohort and tier.
• Collaborate with Loyalty, PRO, Marketing, FP&A, and IT to translate insights into actions.
• Design and analyze A/B tests and experiments; use causal inference when available.
• Present findings and recommendations to business stakeholders.

Tools

Claude

Codex

Job description

This position is responsible for building and maintaining the models and measurement frameworks that support Floor & Decor's PRO loyalty program, including member behavior across the program lifecycle, reward redemption and breakage, response to program mechanics, and customer lifetime value. Working cross-functionally with Loyalty/CX, PRO, Marketing/CRM, FP&A, and IT, this role delivers the analysis and models that inform program design decisions, identify at-risk members, and drive incremental improvement across the customer journey.

Minimum Eligibility Requirements

• Bachelor's degree in Statistics, Data Science, Computer Science, Mathematics, Economics, or a related quantitative field (Master's degree a plus); relevant experience can be substituted for the required education on the basis of one calendar year of experience for one academic year of education.
• 3+ years of relevant experience in data science, applied statistics, or advanced analytics required, or an equivalent combination of education and experience sufficient to perform the essential functions of the job, as determined by the company.
• Strong proficiency in SQL.
• Experience with at least one statistical/analytical programming language (Python and/or R).
• Experience with AI-assisted analysis tools (e.g., Claude, Codex) to accelerate data exploration, modeling, and reporting
• Demonstrated ability to persuade business leaders through compelling data visualizations.
• Experience with statistical inference and regression including predictive modeling, feature selection, and feature extraction.
• Loyalty or subscription/membership experience as well as CRM and lifecycle marketing analytics experience strongly preferred.
• Fluency with program economics: earn/burn mechanics, breakage, margin impact.
• Experience with churn & retention modeling, including experience identifying the reasons for churn and critical rescue points.
• Experience with customer lifetime value & propensity modeling.
• Experience designing, executing, and analyzing A/B tests and other experiments; familiarity with causal inference methodology a plus.
• Demonstrated ability to translate data into strategic business outcomes, with a structured and data-driven approach to business problem solving.
• Must be highly analytical, enjoy working directly with data, and be able to provide data-driven rationale for new projects, initiatives, and marketing strategies.
• Strong communication skills, with the ability to present technical findings to both technical and non-technical audiences.
• Must be able to work independently as well as cross-functionally with multiple teams, from analysis design through execution to measurement of results.
• Must be organized, detail-oriented, and possess strong problem-solving skills.
• Ability to multi-task and work in a fast-paced environment.
• Personal integrity, humility, and an appreciation for the power of true teamwork.

Essential Job Functions

• Model member behavior across the program lifecycle: enrollment, activation, engagement depth, tier progression and demotion risk. Maintain the program health view used by Loyalty, PRO, and Marketing leadership.
• Model reward redemption and breakage behavior by cohort, tier, and reward type; partner with FP&A on program financial planning, to supply the behavioral inputs underlying those forecasts.
• Quantify and predict how members respond to program mechanics, e.g. earn rates, tier thresholds, reward structures, to inform design decisions before launch and measure behavior change after.
• Define test/incrementality measurement of program optimizations and tests.
• Customer Lifetime Value modeling: a single org-wide definition maintained as the shared input to loyalty, marketing investment, and financial planning.
• Build and maintain PRO retention and churn models that identify at-risk customers and members early enough to act, including the drivers of churn and the points where intervention is still possible.
• Design and evolve customer segmentation frameworks using behavioral, transactional, and demographic data to support targeted marketing and personalization.
• Develop share-of-wallet and growth-potential models to estimate spend headroom and identify high-value PRO accounts; partner with PRO leadership to translate model output into targeting strategy. Standard PRO reporting and list generation is owned by Customer Analytics & Insights.
• Develop propensity models — purchase, churn, engagement, enrollment — that produce scored customer files consumable by marketing, PRO, ML Ops, and store teams.
• Partner with IT and Data Engineering to close gaps across internal data technology stack and third-party sources.
• Partner cross-functionally with Marketing/CRM, IT, PRO, Finance, and Loyalty stakeholders to translate analytical findings into clear, actionable business recommendations.
• Present findings and recommendations to business stakeholders and leadership in a clear, actionable way, tailored to the audience.
• Maintain clear documentation of methodologies, model assumptions, and limitations to ensure reproducibility and continuity.
• Stay abreast of industry trends and best practices in customer analytics, loyalty measurement, and applied data science.
• Be compliant with all appropriate Privacy Preferences and Security protocols.

Working Conditions (travel, hours, environment)

• Limited travel required including air and car travel
• While performing the duties of this job, the employee is occasionally exposed to a warehouse environment and moving vehicles. The noise level in the work environment is typically quiet to moderate.

Physical/Sensory Requirements

Sedentary Work – Ability to exert 10 - 20 pounds of force occasionally, and/or negligible amount of force frequently to lift, carry, push, pull or otherwise move objects. Sedentary work involves sitting most of the time but may involve walking or standing for brief periods of time.

Benefits & Rewards

• Bonus opportunities at every level
• Non-traditional retail hours (we close at 7p!)
• Relocation opportunities across the country
• 401k with discretionary company match
• Employee Stock Purchase Plan
• Referral Bonus Program
• 80 hrs. annualized paid vacation (full-time associates)
• 4 paid holidays per year (full-time hourly store associates only)
• 1 paid personal holiday of associate’s choice and Volunteer Time Off program
• Medical, Dental, Vision, Life and other Insurance Plans (subject to eligibility criteria)

Floor & Decor provides equal employment opportunities to all associates and applicants without regard to age, race, color, religion or creed, national origin or ancestry, sex (including pregnancy), sexual orientation, gender, gender identity, disability, veteran status, genetic information, ethnicity, citizenship, or any other category protected by law.

This policy applies to all areas of employment, including recruitment, testing, screening, hiring, selection for training, upgrading, transfer, demotion, layoff, discipline, termination, compensation, benefits and all other privileges, terms and conditions of employment. This policy and the law prohibit employment discrimination against any associate or applicant on the basis of any legally protected status outlined above.